• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.419-434
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• 2020

The purpose of the study is to design and propose metadata standard for building AI training dataset of landmark images. In order to achieve the purpose, we first examined and analyzed the state of art of the types of image retrieval systems and their indexing methods, comprehensively. We then investigated open training dataset and machine learning tools for image object recognition. Sequentially, we selected metadata elements optimized for the AI training dataset of landmark images and defined the input data for each element. We then concluded the study with implications and suggestions for the development of application services using the results of the study.

• Korean Journal of Optics and Photonics
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• v.9 no.6
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• pp.385-389
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• 1998

In this paper, we propose an optical correlator system using volume holograms for database of matched filters. Optical correlator has high speed and parallel processing characteristics of optics. Matched filters are recorded into a volume hologram that can store data with high density, transfer them with high speed, and select a randomly chosen data element. The multiple reference images of database are prerecorded in a photorefractive crystal in the form of Fourier transform images, simply by passing the image displayed in a spatial light modulator through a Fourier transform lens. The angular multiplexing method for multiple holograms of database can be achieved by rotating the crystal by use of a step motor. Experimental results show that the proposed system can be used for the fingerprint recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.834-839
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• 2009

It is a key element that the problem of emotional feature extraction based on facial image to recognize a human emotion status. In this paper, we propose an Advanced AAM that is improved version of proposed Facial Expression Recognition Systems based on Bayesian Network by using FACS and AAM. This is a study about the most efficient method of optimal facial feature area for human emotion recognition about random user based on generalized HCI system environments. In order to perform such processes, we use a Statistical Shape Analysis at the normalized input image by using Advanced AAM and FACS as a facial expression and emotion status analysis program. And we study about the automatical emotional feature extraction about random user.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.499-505
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• 2012

Objective: Research on the transformation of interaction between mobile machines and users through analysis on current gesture interface technology development trend. Background: For smooth interaction between machines and users, interface technology has evolved from "command line" to "mouse", and now "touch" and "gesture recognition" have been researched and being used. In the future, the technology is destined to evolve into "multi-modal", the fusion of the visual and auditory senses and "3D multi-modal", where three dimensional virtual world and brain waves are being used. Method: Within the development of computer interface, which follows the evolution of mobile machines, actively researching gesture interface and related technologies' trend and development will be studied comprehensively. Through investigation based on gesture based information gathering techniques, they will be separated in four categories: sensor, touch, visual, and multi-modal gesture interfaces. Each category will be researched through technology trend and existing actual examples. Through this methods, the transformation of mobile machine and human interaction will be studied. Conclusion: Gesture based interface technology realizes intelligent communication skill on interaction relation ship between existing static machines and users. Thus, this technology is important element technology that will transform the interaction between a man and a machine more dynamic. Application: The result of this study may help to develop gesture interface design currently in use.

• Korean Institute of Interior Design Journal
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• no.39
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• pp.116-123
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• 2003

The purpose of this study is to demonstrate the relationship between the results of the analysis of the overseas railroad station buildings, which was conducted using the factors of environmental cognition for the purpose of designing an interior environment for the Incheon International Airport Railroad station that will be newly constructed, and the plan that could be applied to the design of interior environment for the airport railroad station. The station with a complex interior space layout and relatively larger space tends to be difficult to predict or forecast passenger's needs or recognition element in approaching stage of intoner environment design since the human's biological memory system is greatly affected by such factors. Cognitive approach at empirical standpoint would possibly create the design, of which elements will Implement the functions of their own as such approach enables necessary information to be structured in a systematical way and manner In implementing interior environment design for such stations to be built for the first time in Korea, behavioral approach based on systematic theory proved to be very crucial. Under such a background, the study was aimed at extracting the assessment elements for interior environment design, then setting the frame of cognitive approach to eventually propose the guideline in approaching to interior environment design.

• Korean Institute of Interior Design Journal
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• v.14 no.4 s.51
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• pp.122-133
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• 2005

This study could begin with the improvement of computer graphic technology The graphic technology is the standards of computer technology level and up-to-date technology intensive. Above all, the technology of virtual reality has developed rapidly and the development of the program has changed from professional one only for the experts to easy of access ones for the space designers. Moreover, the program which major internet user's can experience the virtual model has been made, as the development of virtual reality technology that is based on the web. These graphic technology and the development of the web helped to extract human experiences on the space design step. However, to find the meeting point with real recognition is not easy though the virtual reality technology develops. Because the real space is made up of various senses that people feel in their surroundings. But, this study was possible because most of the space recognition is based on the visual organ, even though it can't satisfy all sensible factors that we feel in reality. Therefore, the significant of this study is the standards and criteria of evaluation, the technological proposal, expecting to make more advanced alternative design than before.

• The Plant Pathology Journal
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• v.37 no.3
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• pp.291-298
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• 2021

False smut caused by Ustilaginoidea virens is an important rice fungal disease that significantly decreases its production. In the recent past, conventional methods have been developed for its detection that is time-consuming and need high-cost equipments. The research and development in nanotechnology have made it possible to assemble efficient recognition interfaces in biosensors. In this study, we present a simple, sensitive, and selective oxidized graphene-based geno-biosensor for the detection of rice false smut. The biosensor has been developed using a probe DNA as a biological recognition element on paper electrodes, and oxidized graphene to enhance the limit of detection and sensitivity of the sensor. Probe single-stranded DNA (ssDNA) and target ssDNA hybridization on the interface surface has been quantitatively measured with the electrochemical analysis tools namely, cyclic voltammetry, and linear sweep voltammetry. To confirm the selectivity of the device, probe hybridization with non-complementary ssDNA target has been studied. In our study, the developed sensor was able to detect up to 10 fM of target ssDNA. The paper electrodes were employed to produce an effective and cost-effective platform for the immobilization of the DNA and can be extended to design low-cost biosensors for the detection of the other plant pathogens.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.122-128
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• 2023

The target must be located within the main-lobe of the antenna in order to measure the direction of the target by using sum-delta monopulse technique. The most common way if the target is located within the main-lobe is to compare the amplitude of the sum channel received signal with the delta channel received signal. However, in the case of the single-ring circular array antenna, it is difficult to apply the conventional method due to its structural limitation where antenna elements do not exist in the center of the array. In this paper, we proposed a novel method to identify whether a target is located within the main-lobe by appropriately adjusting the feeding amplitude of each element constituting the single-ring circular array antenna through the particle swarm optimization method. Simulation results showed that the proposed method can determine whether the target is located within the main-lobe of the single-ring circular array antenna.

• International journal of advanced smart convergence
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• v.11 no.4
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• pp.68-80
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• 2022

Since the launch of AI, technology development to implement complete and sophisticated AI functions has continued. In efforts to develop technologies for complete automation, Machine Learning techniques and deep learning techniques are mainly used. These techniques deal with supervised learning, unsupervised learning, and reinforcement learning as internal technical elements, and use the Big-data Analysis method again to set the cornerstone for decision-making. In addition, established decision-making is being improved through subsequent repetition and renewal of decision-making standards. In other words, big data analysis, which enables data classification and recognition/recognition, is important enough to be called a key technical element of AI function. Therefore, big data analysis itself is important and requires sophisticated analysis. In this study, among various tools that can analyze big data, we will use a Python program to find out what variables can affect addiction according to smartphone use in a decision tree environment. We the Python program checks whether data classification by decision tree shows the same performance as other tools, and sees if it can give reliability to decision-making about the addictiveness of smartphone use. Through the results of this study, it can be seen that there is no problem in performing big data analysis using any of the various statistical tools such as Python and R when analyzing big data.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.5
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• pp.510-517
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• 2001

This paper describes an initial study for the application of eddy current pattern recognition approaches to more realistic flaw characterization in steam generator tubes. For this purpose, finite-element model-based theoretical eddy current testing (ECT) signals are simulated from 5 types of OD flaws with the variation in flaw size parameters and testing frequency. In addition, three kinds of software are developed for the convenience in the application of steps in pattern recognition approaches such as feature extraction feature selection and classification by probabilistic neural networks (PNNs). The cross point of the ECT signals simulated from flaws with non-symmetric cross-sections shows the deviation from the origin of the impedance plane. New features taking advantages of this phenomenon are added to complete the feature set with a total of 18 features. Then, classification with PNNs are performed based on this feature set. The PNN classifiers show high performance for the identification of symmetry in the cross-section of a flaw. However, they show very limited success in the interrogation of the sharpness of flaw tips.