• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.69-78
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• 2021

The development of smart healthcare wearables for health is accelerating. Among them, many wearable products using EMS electrical stimulation, which is one of the active research fields, have been released. However, the EMS wearable, which has been studied or released, is released in a comprehensive full-body suit that does not focus on muscle segmentation or a belt that covers the entire abdomen. Therefore, this study intends to use two breathing methods by applying an EMS pattern that subdivides specific muscles and attach a stretch sensor that can measure breathing to the abdominal pressure belt. The measurement method was conducted by inhaling and exhaling, and the subjects were 10 men in their 20s with healthy bodies. As a result of this study, the sensor's sensitivity was 5 and 3 mm, and the basic sensor in both thoracic and abdominal breathings and the EMS abdominal pressure belt showed improved respiration activation after applying electrical stimulation before and after application. It is concluded that, because of the two patterns produced based on the physical function, the difference in respiration activation effect and sensitivity between sensors could be confirmed with three sensors rather than not applying electrical stimulation suitable for the respiration method. Based on the results of this study, a follow-up study aims to develop breathing smart clothing that can be monitored in real time in clothing-type wearable products that incorporate EMS patterns and stretch sensors.

• Journal of the Korean Geosynthetics Society
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• v.21 no.1
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• pp.1-10
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• 2022

In this study, a model parameter evaluation method using relative density was proposed to utilize applicable UBC3D-PLM for liquefaction behavior. In addition, dynamic effective stress analysis, that is, liquefaction analysis, was performed on the case of the liquefaction occurrence region where acceleration and pore water pressure were measured, and compared with the actual measurement and the existing Finn analysis results. Through this study, it was found that the proposed method can easily evaluate the necessary parameters required by the related model and predict the pore water pressure behavior in the region where liquefaction occurs. In addition, in the case of the study area, both measurements and numerical analysis showed that liquefaction occurred when a certain amount of time elapsed after the earthquake acceleration reached the maximum value. In the case of UBC3D-PLM applied in this study, the excess pore water pressure behavior similar to the actual measurement was predicted, and the occurrence of liquefaction was evaluated in the same way as the actual measurement. In particular, although the excess pore water pressure in the sand layer was greater, the phenomenon in which liquefaction occurred in the silt layer was accurately realized. It is expected that the proposed model parameter evaluation method and finite element analysis applying UBC3D-PLM can be used to select the liquefaction reinforcement region in the future seismic design and reinforcement by evaluating the liquefaction occurrence region similarly to the real one.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.217-226
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• 2022

In the view of the application of high-precision spatial information production, UAV (Umanned Aerial Vehicle)-Photogrammetry has a problem in that it lacks specific procedures and detailed regulations for quantitative quality verification methods or certification of captured images. In addition, test tools for UAV image quality assessment use only the GSD (Ground Sample Distance), not MTF (Modulation Transfer Function), which reflects image resolution and contrast at the same time. This fact makes often the quality of UAV image inferior to that of manned aerial image. We performed MTF and GSD analysis simultaneously using a siemens star to confirm the necessity of MTF analysis in UAV image quality assessment. The analyzing results of UAV images taken with different payload and sensors show that there is a big difference in σ_MTF values, representing image resolution and the degree of contrast, but slightly different in GSD. It concluded that the MTF analysis is a more objective and reliable analysis method than just the GSD analysis method, and high-quality drone images can only be obtained when the operator make images after judging the proper selection the sensor performance, image overlaps, and payload type. However, the results of this study are derived from analyzing only images acquired by limited sensors and imaging conditions. It is therefore expected that more objective and reliable results will be obtained if continuous research is conducted by accumulating various experimental data in related fields in the future.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.33-40
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• 2021

Automatic Speech Recognition(ASR) is a technology that analyzes human speech sound into speech signals and then automatically converts them into character strings that can be understandable by human. Speech recognition technology has evolved from the basic level of recognizing a single word to the advanced level of recognizing sentences consisting of multiple words. In real-time voice conversation, the high recognition rate improves the convenience of natural information delivery and expands the scope of voice-based applications. On the other hand, with the active application of speech recognition technology, concerns about related cyber attacks and threats are also increasing. According to the existing studies, researches on the technology development itself, such as the design of the Automatic Speaker Verification(ASV) technique and improvement of accuracy, are being actively conducted. However, there are not many analysis studies of attacks and threats in depth and variety. In this study, we propose a cyber attack model that bypasses voice authentication by simply manipulating voice frequency and voice speed for AI voice recognition service equipped with automated identification technology and analyze cyber threats by conducting extensive experiments on the automated identification system of commercial smartphones. Through this, we intend to inform the seriousness of the related cyber threats and raise interests in research on effective countermeasures.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.835-850
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• 2022

Microplastics have arisen as a worldwide environmental concern, becoming ubiquitous in all marine compartments, and various researches on monitoring marine microplastics are being actively conducted worldwide. Recently, application of a remote detection technology that enables large-scale real-time observation to marine plastic monitoring has been conducted overseas. However, in South Korea, there is little information linking remote detection to marine microplastics and some field studies have demonstrated remote detection of medium- and large-sized marine plastics. This study introduces research cases with remote detection of marine plastics in South Korea and overseas, investigates potential feasibility of using the remote detection technology to marine microplastic monitoring, and suggests some future works to monitor marine microplastics with the remote detection.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.725-735
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• 2022

Currently, disasters occurring in Korea are characterized by unpredictability and complexity. Due to these features, property damage and human casualties are increasing. Since the initial response process of these disasters is directly related to the scale and the spread of damage, optimal decision-making is essential, and information of the site must be obtained through timely applicable sensors. However, it is difficult to make appropriate decisions because indiscriminate information is collected rather than necessary information in the currently operated Disaster and Safety Situation Office. In order to improve the current situation, this study proposed a framework that quickly collects various disaster image information, extracts information required to support decision-making, and utilizes it. To this end, a web-based display system and a smartphone application were proposed. Data were collected close to real time, and various analysis results were shared. Moreover, the capability of supporting decision-making was reviewed based on images of actual disaster sites acquired through CCTV, smartphones, and UAVs. In addition to the reviewed capability, it is expected that effective disaster management can be contributed if institutional mitigation of the acquisition and sharing of disaster-related data can be achieved together.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.196-205
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• 2021

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.164-173
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• 2021

Recently, as underground space safety issues such as sink hole, ground subsidence and damage to old underground facilities have been increasing in urban areas, the precise management of underground facilities ins more required. Thus, this study developed a function to that, visualize on Integration Map of Underground Geospatial Information a real-time survey data of underground facilities acquired on site or underground facility survey data acquired through on-site survey after underground facility exploration and developed a function convert to surveying-results. In addition, using the on-site survey performance utilization function in connection with the Integration Map of Underground Geospatial Information developed through this study, the surveying -results obtained with the Total-station at the water pipeline burial construction site in Eunpyeong-gu, Seoul are visualized on the Integration Map of Underground Geospatial Information and On-site verification was performed by converting spatial-information performance files and transmitting the Integration Map of Underground Geospatial Information to the mobile center. Based on this, it was possible to verify the work procedure using the surveying-results in the area where the Integration Map of Underground Geospatial Information was built, and to review the direction of future improvement directions.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.57-64
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• 2022

This scientific article is devoted to the study of the legal significance of such a category of legal status of the purchaser of another's thing, as its good faith. The essence of this phenomenon has been studied, it has been established that the criterion of good faith attaches significant importance to the claims of the participants of these relations for the acquisition or preservation of private property rights. The paper emphasizes that, in addition to the importance of good conscience at the time of possession of another's thing, which gives legal certainty the possibility of registration of the title and is part of the actual composition for the acquisition of property or the right of ancient possession, bona fides also characterizes the behavior of the occupier. In this case, good conscience only has some legal consequences when it is opposed to subjective law. Under such conditions, it acquires direct legal significance, including as a condition for the acquisition and protection of rights. Good faith possession of another's property is an internal indicator of the subject's awareness of a certain property status. This sense, the article assesses this status from the standpoint of the scientific concept of the visibility of law. According to this theory, prescription is also considered as a consequence of the appearance of law, however, because it arises and lasts against the will of the parties and despite their awareness of this fact. Therefore, bona fide continuous and open possession of property as one's own, during the acquisition period, was most significantly associated with the appearance of property. Therefore, the concept of good faith, in the sense of personal perception of real values, is closely related to the principle of protection of the appearance of law, as it is aimed at understanding it by third parties. The paper notes certain differences in the application of the theory of the appearance of the right in the acquisition of property by a bona fide purchaser from an unauthorized alienator and the acquisitive prescription. It is emphasized that such a mechanism must be used in presuming the attitude to the thing as its own, by the holder of movable property. But there should be exceptions to the rule, in particular, if the owner has grounds for vindication of the thing.