• Proceedings of the IEEK Conference
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• summer
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• pp.410-415
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• 2004

Employing knowledge of adaptive possibilities of agents in multi-agents system, we have explored new aspects of distributed modular systems for building ubiquitous heterogeneous robotic systems using intelligent building blocks (I-BLOCKS) [1] as reconfigurable modules. This paper describes early technological approaches related to technical design, experimental developments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop modular robotic systems. The processing technology presented in this paper is embedded inside each $DUPLO^1$ brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Block in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can easily do 'programming by building' and thereby create specific functionalities of a modular robotic structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modern artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing modular robotic system with different types of morphology, functionality and behavior. To assess these potential I-BLOCKS possibilities, the paper presents a limited range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular robots. The paper also reports briefly about earlier experiments of I-BLOCKS created on users' natural inspiration by a just defined concept of modular artefacts.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1207-1212
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• 2015

In this paper, we propose three-dimensional (3D) visualization and recognition techniques of micro-objects under photon-starved conditions using photon counting integral imaging microscopy. To capture high resolution 2D images with different perspectives in the proposed method, we use Synthetic Aperture Integral Imaging (SAII). Poisson distribution which is mathematical model of photon counting imaging system is used to extract photons from the images. To estimate 3D images with 2D photon counting images, the statistical estimation is used. Therefore, 3D images can be obtained and visualized without any damage under photon-starved conditions. In addition, 3D object recognition can be implemented using nonlinear correlation filters. To prove the usefulness of our technique, we implemented the optical experiment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.8-16
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• 2011

Image inpainting is a technique for removing damaged regions and reconstructing them with visually plausible backgrounds. However, if size of the damaged regions for reconstructing is large, the unexpected results can be obtained due to disconnected structures within reconstructed regions. In this paper, by considering spatial distance information between candidate patches and a damaged patch as well as pixel value difference, an exemplar-based image inpainting using multiple patches is proposed. In conventional exemplar-based image inpainting method, implausible results such as blocking effects or repetition of reconstructed patch may occur by using inappropriately selected single patch. To improve the exemplar-based method, the weighted sum of multiple patches considering both the spatial distance and the pixel value difference between the target patch and the candidate patches is utilized. Experimental results have shown that the proposed method produces better performance of image inpainting than the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2571-2578
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• 2014

In this paper, we propose a computational generation method of elemental images for time-multiplexed 3D integral imaging display based lens division. In the proposed method, we analyze the image formation between 3D object and elemental images based on ray optics. Based on the analyzed formation, we generate the elemental image set for time-multiplexed display. Positions of an object point picked up in proposed method is shifted for half size of lens divided from those in conventional method when generating elemental images. To show the usefulness of the proposed method, we carry out the preliminary experiments and present the results.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.89-97
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• 2021

Recently, as the importance of forced indoor living has increased in the untact era, the connection and relationship between space environments is increasing. That is, the smart interaction environment for providing services in various spaces collects and processes a number of surrounding environment information through various sensors to provide desired information according to the required place and time. In this environment, a new type of interaction paradigm is needed for the user to select and focus on environmental information. In this paper, we provide guidelines based on models and patterns for designing various interactions around space. Through interaction model-based technology, we provide guidelines for space-oriented interaction design. We propose an ideal interaction environment through guideline-based patterns and templates. Finally, by providing a space-oriented interaction environment suitable for smart interaction, users can freely obtain desired information.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.55-65
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• 2011

In this paper, a novel method of marker detection robust against marker occlusion in augmented reality is proposed. the proposed method consists of four steps. In the first step, in order to effectively detect an occluded marker, we first utilize the Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) for detecting matching points between an enrolled marker and an input images with an occluded marker. In the second step, we apply the Principal Component Analysis (PCA) for eliminating outlier of the matching points in the enrolled marker. And then matching points are projected to the first and second axis for longest value and the shortest value of an ellipse are determined by average distance between the projected points and a center of the points. In the third step, Convex-hull vertices including matching points are considered as polygon vertices for estimating a geometric affine transformation. In the final step, by estimating the geometric affine transformation of the points, a marker robust against a marker occlusion is detected. Experimental results have shown that the proposed method effectively detects occlude markers.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.70-78
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• 2009

In this paper, we propose a novel method for eye detection using two texture filters considering textural and structural characteristics of eye regions. The human eyes have two characteristics: 1) the eyes are horizontally long and 2) the pupas are of circular shapes. By considering these two characteristics of human eyes, two texture filters are utilized for the eye detection. One is Gabor filter for detecting eye shapes in horizontal direction. The other is ART descriptor for detecting pupils of circular shape. In order to effectively detect eye regions, the proposed method consists of four steps. The first step is to extract facial regions using AdaBoost method. The second step is to normalize the illumination by considering local information. The third step is to estimate candidate regions for eyes, by merging the results from two texture filters. The final step is to locate exact eye regions by using geometric information of the face. As experimental results, the performance of the proposed method has been improved by 2.9~4.4%, compared to the existing methods.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.127-132
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• 2011

In this paper, we propose a novel method of adult image classification by combining skin color regions and edges in an input image. The proposed method consists of four steps. In the first step, initial skin color regions are detected by logical AND operation of all skin color regions detected by the existing methods of skin color detection. In the second step, a skin color probability map is created by modeling the distribution of skin color in the initial regions. Then, a binary image is generated by using threshold value from the skin color probability map. In the third step, after using the binary image and edge information, we detect final skin color regions using a region growing method. In the final step, adult image classification is performed by support vector machine(SVM). To this end, a feature vector is extracted by combining the final skin color regions and neighboring edges of them. As experimental results, the proposed method improves performance of the adult image classification by 9.6%, compared to the existing method.

• Steel and Composite Structures
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• v.50 no.3
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• pp.281-298
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• 2024

Stainless steel bolts (SSB) are increasingly utilized in bolted steel connections due to their good mechanical performance and excellent corrosion resistance. Fire accidents, which commonly occur in engineering scenarios, pose a significant threat to the safety of steel frames. The post-fire behavior of SSB has a significant influence on the structural integrity of steel frames, and neglecting the effect of temperature can lead to serious accidents in engineering. Therefore, it is important to evaluate the performance of SSB at elevated temperatures and their residual strength after a fire incident. To investigate the mechanical behavior of SSB after fire, 114 bolts with grades A4-70 and A4-80, manufactured from 316L austenitic stainless steel, were subjected to elevated temperatures ranging from 20℃ to 1200℃. Two different cooling methods commonly employed in engineering, namely cooling at ambient temperatures (air cooling) and cooling in water (water cooling), were used to cool the bolts. Tensile tests were performed to examine the influence of elevated temperatures and cooling methods on the mechanical behavior of SSB. The results indicate that the temperature does not significantly affect the Young's modulus and the ultimate strength of SSB. Up to 500℃, the yield strength increases with temperature, but this trend reverses when the temperature exceeds 500℃. In contrast, the ultimate strain shows the opposite trend. The strain hardening exponent is not significantly influenced by the temperature until it reaches 500℃. The cooling methods employed have an insignificant impact on the performance of SSB. When compared to high-strength bolts, 316L austenitic SSB demonstrate superior fire resistance. Design models for the post-fire mechanical behavior of 316L austenitic SSB, encompassing parameters such as the elasticity modulus, yield strength, ultimate strength, ultimate strain, and strain hardening exponent, are proposed, and a more precise stress-strain model is recommended to predict the mechanical behavior of 316L austenitic SSB after a fire incident.