• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.5 no.2
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• pp.37-46
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• 1987

The single photo method has a lot of applications in forestry, traffic accident managements, industry, criminal investigation, and in daily life. In this study a new single photo method was developed by classifying into the Space resection method and the 2 Dimensional Perspective Transformation method. Metric and nonmetric cameras were used to analyse the accuracy by means of single photo method, and the errors in coordinates and lengths were studied by changing the number and arrangement of control points to obtain the optimum condition for the single photo method. The influence of number and arrangement of control points on the accuracy was relatively small in case of the Metric WILD P31 and ASAHI PENTAX 6$\times$7 cameras, where as for errors it was a major factor in the Non-metric Nikon FM2. To overcome these defects, at least 6 control points should be used for the errors to be convergent and they should be distributed evenly over the surveying area. It was found that accuracy increased as the object to be photographed was placed in the perpendicular direction to the axis of camera.

• Cartoon and Animation Studies
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• s.25
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• pp.87-108
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• 2011

Published comics are widely recognized as a popularity-gaining media as well as Soap opera and the movies, and it also has a established characteristic of category. However, compare to the multimedia such as the movies, soap opera and playes, the research on direction is not yet satisfactory This research mainly tries to investigate on, first, whether the theoretically classified functions do actually practice their parts or not, and else, what other additional functions should be considered, by classifying the set up of basic direction functions, angles and range, which the most-cited angle and distance notion of 'Ahn Su Cheol' in comic education field. First, although we tried to approach with the expectation of angle and distance set up that will have a high frequency of certain set ups according to the atmospheres of comics of genre, unlike the expectation, they are rather displayed depending on the personal taste of the writers. The functional aspects of angles and distance set up are the fixing that are only limited in the space of representation, and it is the set up of physical space that should come first as the function of expressing the intensity. As we investigate the characteristics of comic direction, this research will help the range of comic direction to be broadened.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.1021-1031
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• 2020

With the advent of industry 4.0 technologies like the artificial intelligence and the autonomous flight, 'Urban Air Mobility (UAM)' is being considered as an effective alternative to resolve the ground urban traffic congestion. Accordingly, many companies in the world including Korea are investigating on the development of UAM vehicles and operation systems. In this study, after identifying and classifying the essential elements of the UAM operation, the UAM system operational concept has been derived, then detailed analyses for each element has been performed. Based on the conceptual analysis of the UAM operation system, UAM flight routes in Seoul and Gyeong-In area have been established and confirmed to be operable through the performance analysis of UAM vehicles. The flight route analysis in this study is expected to be applied to UAM flight routes establishment in various cities in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.47-57
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• 2022

UAVs have been deployed various missions such as deception, reconnaissance and attack since they have been applied in battlefield and achieved missions successfully instead of man. In the past, it is impossible for UAVs to conduct autonomous missions or cooperative mission between manned aircraft due to the limitation of the technology. However, theses missions are possible owing to the advance in communication and AI Technology. In this research, we identified the possible cooperative missions between manned and unmanned team based on air-to-air mission. We studied cooperative manned and unmanned tactics about fighter sweep mission which is the core and basic operation among various air-to-air missions. We also developed cooperative tactics of manned and unmanned team by classifying nonstealth and stealth confrontational tactics. Hereafter, we verified the validity of the suggested tactics using computer simulations.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.163-172
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• 2022

Typical anti-jamming technologies based on array antennas, Space Time Adaptive Process (STAP) & Space Frequency Adaptive Process (SFAP), are very effective algorithms to perform nulling and beamforming. However, it does not perform equally well for all types of jamming signals. If the anti-jamming algorithm is not optimized for each signal type, anti-jamming performance deteriorates and the operation stability of the system become worse by unnecessary computation. Therefore, jamming classification technique is required to obtain optimal anti-jamming performance. Machine learning, which has recently been in the spotlight, can be considered to classify jamming signal. In general, performing supervised learning for classification requires a huge amount of data and new learning for unfamiliar signal. In the case of jamming signal classification, it is difficult to obtain large amount of data because outdoor jamming signal reception environment is difficult to configure and the signal type of attacker is unknown. Therefore, this paper proposes few-shot jamming signal classification technique using meta-learning and transfer-learning to train the model using a small amount of data. A training dataset is constructed by anti-jamming algorithm input data within the GNSS receiver when jamming signals are applied. For meta-learning, Model-Agnostic Meta-Learning (MAML) algorithm with a general Convolution Neural Networks (CNN) model is used, and the same CNN model is used for transfer-learning. They are trained through episodic training using training datasets on developed our Python-based simulator. The results show both algorithms can be trained with less data and immediately respond to new signal types. Also, the performances of two algorithms are compared to determine which algorithm is more suitable for classifying jamming signals.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.91-97
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• 2009

This paper proposes novel FE-CBIRS that finds best position of a cut to be retrieved based on color feature distribution in digital contents of IPTV. Conventional CBIRS have used a method that utilizes both color and shape information together to classify images, as well as a method that utilizes both feature information of the entire region and feature information of a partial region that is extracted by segmentation for searching. Also, in the algorithm, average, standard deviation and skewness values are used in case of color features for each hue, saturation and intensity values respectively. Furthermore, in case of using partial regions, only a few major colors are used and in case of shape features, the invariant moment is mainly used on the extracted partial regions. Due to these reasons, some problems have been issued in CBIRS in processing time and accuracy so far. Therefore, in order to tackle these problems, this paper proposes the FE-CBIRS that makes searching speed faster by classifying and indexing the extracted color information by each class and by using several cuts that are restricted in range as comparative images.

• ETRI Journal
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• v.32 no.6
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• pp.881-890
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• 2010

Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms; for example, a person smoking in a room may trigger a typical fire alarm system. In order to manage false alarms of conventional fire detection systems, a computer vision-based fire detection algorithm is proposed in this paper. The proposed fire detection algorithm consists of two main parts: fire color modeling and motion detection. The algorithm can be used in parallel with conventional fire detection systems to reduce false alarms. It can also be deployed as a stand-alone system to detect fire by using video frames acquired through a video acquisition device. A novel fire color model is developed in CIE $L^*a^*b^*$ color space to identify fire pixels. The proposed fire color model is tested with ten diverse video sequences including different types of fire. The experimental results are quite encouraging in terms of correctly classifying fire pixels according to color information only. The overall fire detection system's performance is tested over a benchmark fire video database, and its performance is compared with the state-of-the-art fire detection method.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.743-746
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• 2004

This study is generally purposed to develop a mobile augmentative and alternative communication system (hereinafter referred to as 'a mobile AAC system'). Also the device is aimed as a mobile AAC system for helping communication of persons who suffer from speech disorders in a free and convenient manner. One thing firstly considered for a successful AAC system is selection of vocabularies. For this purpose, the above researchers collected utterances in actual situations to select vocabularies of higher frequencies. For generation of sentences by maximizing the use of limited space in the AAC system, this study specifically presents a method of predicting predictions. This method includes selecting vocabulary and classifying it by domains so as to meet the characteristics of the mobile AAC communication, using a noun thesaurus for semantic analysis, and building a sub-category dictionary. Predicting predicates by selecting symbols in accordance with this method is tested and the utility thereof is confirmed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.742-762
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• 2015

In this study, we propose a distance metric learning approach called discriminant metric learning (DML) for face verification, which addresses a binary-class problem for classifying whether or not two input images are of the same subject. The critical issue for solving this problem is determining the method to be used for measuring the distance between two images. Among various methods, the large margin nearest neighbor (LMNN) method is a state-of-the-art algorithm. However, to compensate the LMNN's entangled data distribution due to high levels of appearance variations in unconstrained environments, DML's goal is to penalize violations of the negative pair distance relationship, i.e., the images with different labels, while being integrated with LMNN to model the distance relation between positive pairs, i.e., the images with the same label. The likelihoods of the input images, estimated using DML and LMNN metrics, are then weighted and combined for further analysis. Additionally, rather than using the k-nearest neighbor (k-NN) classification mechanism, we propose a verification mechanism that measures the correlation of the class label distribution of neighbors to reduce the false negative rate of positive pairs. From the experimental results, we see that DML can modify the relation of negative pairs in the original LMNN space and compensate for LMNN's performance on faces with large variances, such as pose and expression.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.2
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• pp.103-109
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• 2013

In this study, the three sounds effects on subjects due to EEG type, and it researched to find optimal sound to increase their amenity and productivity. EEG and HRV were compared and analyzed in the environmental test room by classifying subjects into two type: A and B. The condition of the environmental test room was in temperature $31[^{\circ}C]$, relative humidity 50[RH%], air current speed 0.02[m/s] and illuminance 1000[lux] with setting up three different sounds which are U type sound, V type sound and Z type sound. The result of this study, at U type sound for A and B type, relative $M{\alpha}$ wave, relative $M{\beta}$ wave and SEF50 were revitalized. Also at Z type sound for A and B type, stress index, fatigue degree and HRT were decreased and SDNN was revitalized. Therefore U type sound is very effective to increase amenity, productivity and concentration, and Z type sound is very effective to decrease stress and fatigue degree.