• KIPS Transactions on Computer and Communication Systems
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• v.6 no.8
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• pp.359-368
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• 2017

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.85-101
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• 2019

Recently, thank to the popularization of light-weight drone through the significant developments in computer technologies as well as the advanced automated procedures in photogrammetry, Unmanned Aircraft Systems have led to a growing interest in industry as a whole. Documentation, maintenance, and restoration projects of large scaled cultural property would required accurate 3D phenomenon modeling and efficient visual inspection methods. The object of this study verify on the accuracies achieved of 3D phenomenon reconstruction as well as on the validity of the preservation, maintenance and restoration of large scaled cultural property by UAS photogrammetry. The test object is cltural heritage(treasure 1324) that is the rock-carved standing Bodhisattva in Soraesan Mountain, Siheung, documented in Goryeo Period(918-1392). This standing Bodhisattva has of particular interests since it's size is largest stone Buddha carved in a rock wall and is wearing a lotus shaped crown that is decorated with arabesque patterns. The positioning accuracy of UAS photogrammetry were compared with non-target total station survey results on the check points after creating 3D phenomenal models in real world coordinates system from photos, and also the quantified informations documented by Culture Heritage Administration were compared with UAS on the bodhisattva image of thin lines. Especially, tests the validity of UAS photogrammetry as a alternative method of visual inspection methods. In particular, we examined the effectiveness of the two techniques as well as the relative fluctuation of rock surface for about 2 years through superposition analysis of 3D points cloud models produced by both UAS image analysis and ground laser scanning techniques. Comparison studies and experimental results prove the accuracy and efficient of UAS photogrammetry in 3D phenomenon modeling, maintenance and restoration for various large-sized Cultural Heritage.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.135-143
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• 2021

Aerospace and geospatial technologies have become more accessible by researchers and agricultural practitioners, and these technologies can play a pivotal role in transforming current pest management practices in agriculture and forestry. During the past 20 years, technologies including satellites, manned and unmanned aircraft, spectral sensors, information systems, and autonomous field equipment, have been used to detect pests and apply control measures site-specifically. Despite the availability of aerospace and geospatial technologies, along with big-data-driven artificial intelligence, applications of such technologies to apple IPM have not been realized yet. Using a case study conducted at the Korea Apple Research Institute, this article discusses the advances and limitations of current aerospace and geospatial technologies that can be used for improving apple IPM.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.1-13
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• 2021

The concept of integrated pest management (IPM) first developed in the 1950s, and the concept of economic control via pest management was established in the 1960s. Research on IPM began in the United States and Europe, and IPM studies in Korea started with citrus insects and paddy field pests following the distribution of high-yield varieties of rice. Apple IPM in Korea began with research on pest control using chemical pesticides and pesticides resistant to insect pests, studies on the ecology of insect pests and their natural enemies, and the exploitation of sex pheromones on insect pests. Since the 1990s, IPM research and field projects have been carried out simultaneously for farming households. In the 2000s, the development of pest monitoring and forecasting models centered on mating disturbances, database programs for pests, and networks for sharing information. IPM technology has expanded via the development of unmanned forecasting systems and automation technologies in the 2010s.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.207-215
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• 2022

This research has been focused on accessing precision and accuracy of UAV (Unmanned Aerial Vehicle)-derived 3-D surveying coordinates. To this end, a highly precise and accurate testing control network had been established by GNSS (Global Navigation Satellite Systems) campaign and its network adjustment. The coordinates of the ground control points and the check points were estimated within 1cm accuracy for 95% of the confidence level. FC330 camera mounted on DJI Phantom 4 repeatedly took aerial photos of an experimental area seven times, and then processed them by two widely used software packages. To evaluate the precision and accuracy of the aerial surveys, 3-D coordinates of the ten check points which automatically extracted by software were compared with GNSS solutions. For the 95% confidence level, the standard deviation of two software's result is within 1cm, 2cm, and 4cm for the north-south, east-west, and height direction, and RMSE (Root Mean Square Error) is within 9cm and 8cm for the horizontal, vertical component, respectively. The interest is that the standard deviation is much smaller than RMSE. The F-ratio test was performed to confirm the statistical difference between the two software processing results. For the standard deviation and RMSE of most positional components, exception of RMSE of the height, the null hypothesis of the one-tailed tests was rejected. It indicates that the result of UAV photogrammetry can be different statistically based on the processing software.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.256-265
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• 2021

Ground, sea and air mobility, such as vehicles, ships, and airplanes, are generally operated by people. Based on the innovative development of autonomous decision-making systems and artificial intelligence (AI) following the recent fourth industrial revolution, research and development on maritime autonomous surface ships (MASS) is been actively performed around the world. Before the realization of the commercialization of MASS in international maritime transport, it is urgent to clarify the characteristics of this ship and its international legal status. This paper aims to analyze the concern of whether a ship without crew members will eventually be operated as a fully unmanned ship or can be recognized as a ship under international law as the number of crew members is gradually reduced owing to the development stage of autonomous ships. Consequently, based on the United Nations Convention on the Law of the Sea (UNCLOS) and the regulations of the International Maritime Organization (IMO), it was found that MASS has the same international legal status as general ships. In addition this paper presents the working principles of enacting and revising the IMO Conventions and international legal measures necessary for the safe operation of MASS.

• Convergence Security Journal
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• v.22 no.4
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• pp.35-44
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• 2022

Among the five promotion strategies of Defense Innovation 4.0(DI 4.0), the military structure/operation optimization strategy aims to innovate the military structure based on advanced science&technology(S&T), and to integrate advanced S&T in the field of defense operation such as education&training and human resource development. As the future battlefield expands to AI-based unmanned/robot combat systems, space, cyberspace, and electromagnetic fields, it is necessary to train officers with the capabilities required in these battlefields. It is necessary to develop capabilities from junior officers who will lead the future battlefield to operating core advanced power based on the 4^th industrial revolution S&T. We review the education system of the military in universities and propose a method of redesigning the education system that is compatible with DI 4.0 and can develop technology-intensive capabilities based on advanced S&T. We propose a operation plan of major and extra-programs that can develop the capabilities of junior officers required for the future battlefield, and also suggest ways to support the army's practical training.

• Journal of Space Technology and Applications
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• v.3 no.3
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• pp.199-212
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• 2023

In contrast to the short-term nature of lunar missions in the past, lunar missions in new space era aim to extend the presence on the lunar surface and to use this capability for the Mars exploration. In order to realize extended human presence on the Moon, production and use of consumables and fuels required for the habitation and transportation using in-situ resources is an important prerequisite. The Global Exploration Roadmap presented by the International Space Exploration Coordination Group (ISECG), which reflects the space exploration plans of participating countries, shows the phases of progress from lunar surface exploration to Mars exploration and relates in-situ resource utilization (ISRU) capabilities to each phase. Based on the ISRU Gap Assessment Report from the ISECG, ISRU technology is categorized into in-situ propellant and consumable production, in-situ construction, in-space manufacturing, and related areas such as storage and utilization of products, power systems required for resource utilization. Among the lunar resources, leading countries have prioritized the utilization of ice water existing in the permanent shadow region near the lunar poles and the extraction of oxygen from the regolith, and are preparing to investigate the distribution of resources and ice water near the lunar south pole through unmanned landing missions. Resource utilization technologies such as producing hydrogen and oxygen from water by hydroelectrolysis and extracting oxygen from the lunar regolith are being developed and tested in relevant lunar surface analogue environments. It is also observed that each government emphasizes the use and development of the private sector capabilities for sustainable lunar surface exploration by purchasing lunar landing services and providing opportunities to participate in resource exploration and material extraction.

• Smart Media Journal
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• v.13 no.3
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• pp.9-17
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• 2024

Due to the recent pandemic and the development of ICT technology, the use of non-face-to-face and unmanned systems is expanding, and it is very important to understand emotions in communication in non-face-to-face situations. As emotion recognition methods for various facial expressions are required to understand emotions, artificial intelligence-based research is being conducted to improve facial expression emotion recognition in image data. However, existing research on facial expression emotion recognition requires high computing power and a lot of learning time because it utilizes a large amount of data to improve accuracy. To improve these limitations, this paper proposes a method of recognizing facial expressions using age and gender, which are image meta information, as a method of recognizing facial expressions with even a small amount of data. For facial expression emotion recognition, a face was detected using the Yolo Face model from the original image data, and age and gender were classified through the VGG model based on image meta information, and then seven emotions were recognized using the EfficientNet model. The accuracy of the proposed data classification learning model was higher as a result of comparing the meta-information-based data classification model with the model trained with all data.