• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.99-105
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• 2008

To achieve autonomous mobile robot navigation, accurate localization technique is the fundamental issue that should be addressed. In augmented reality, the position of a user is required for location-based services. This paper presents indoor localization using infrared reflective artificial landmarks. In order to minimize the disturbance to the user and to provide the ease of installation, the passive landmarks are used. The landmarks are made of coated film which reflects the infrared light efficiently. Infrared light is not visible, but the camera can capture the reflected infrared light. Once the artificial landmark is identified, the camera's relative position/orientation is estimated with respect to the landmark. In order to reduce the number of the required artificial landmarks for a given environment, the pan/tilt mechanism is developed together with the distortion correction algorithm.

• Genomics & Informatics
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• v.9 no.4
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• pp.173-180
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• 2011

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.10a
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• pp.361-368
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• 1998

The purpose of this study is to find out the factors affacting liquefaction potential by using DSC(disturded state concept) method and to verify these results through cyclic shear test (truly triaxial test and cyclic triaxial) on saturated sandy soil. Based on this reserch, the DSC method predictions were found to provide satisfactory correlation with the cyclic shear test. And the relationship between the factors affecting liquefaction characteristics--relative density(Dr0 and initial effective confining pressure and physical properties of the saturated sand --ξD and Dc--is found. If the relative density and the initial effective confining pressure increase, the number of cyclic grows up. This means that Dc is incresed and ξD is decreased. Therefore, the liquefaction potential can be evaluated and the factors affacting liquefaction potential can be investigated by using on DSC method. Finally, it is shown that the DSC method can capture the liquefaction mechanism.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.9
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• pp.65-75
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• 1992

In this paper, we introduce an integrated layout design system, SOLGER. Our system incorporates useful design tools : a powerful layout editor, a coherent access mechanism for large volumes of design data, an incremental design rule checker for hierarchical design environment, node extractor and electrical rule checker, a technology capture which is used for defining technology-specific information, and a procedural design environment for user customization. Also, we present a modified corner-stitching data structure which allows 45$^{\circ}$-angled bilateral edges. Users are provided with a multi-window design environment and a menu-driven interface. SOLGER is being used for VLSI designs practically.

• Land and Housing Review
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• v.11 no.1
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• pp.39-48
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• 2020

Main research question of this study is about whether gated community (GC) as private urban governance gets along with local public goods by locating near to them. We examine this question through testing the Tiebout hypothesis from case study of Seoul, capital city of South Korea, in which GCs are so common to test the assumption empirically. For this, we examine the meaning of GC in 3 Es viewpoints; conceptualize the framework of Tieboutian co-evolution of GC and local public goods by hedonic price modeling. As a result, possibilities are found that GCs are to be seen from different point of view, viz. co-evolutionary mechanism between private and public governance; GCs effectively capture and represent the demand of residents for local public goods through voting by their collective locational choice. It allows us different kind of approach to investigate APTs as a co-evolutionary form of private and public urban order rather than seeing them only as a tool of speculative investment, particularly in rapidly urbanizing countries like Korea.

• Steel and Composite Structures
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• v.11 no.3
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• pp.233-250
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• 2011

An experimental study has been carried out to reveal the shear-bond failure mechanism of composite deck slabs. Thirteen full scale simply supported composite slabs are studied experimentally, with the influence parameters like span length, slab depth, shear span length and end anchorage provided by steel headed studs. A dozen of strain gauges and LVDTs are monitored to capture the strain distribution and variation of the composite slabs. Before the onset of shear-bond slip, the longitudinal shear forces along the span are deduced and found to be proportional to the vertical shear force in terms of the shear-bond strength in the m-k method. The test results are appraised using the current design procedures. Based on the partial shear-bond connection at the ultimate state, an improved method is proposed by introducing two reduction factors to assess the moment resistance of a composite deck slab. The new method has been validated and the results predicted by the revised method agree well with the test results.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.39-45
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• 2019

This paper presents an optical technique for the three-dimensional (3D) shape inspection of micro solder balls used in ball-grid array (BGA) packaging. The proposed technique uses an optical source composed of spatially arranged light-emitting diodes (LEDs) and the results are derived based on the specular reflection characteristics of the micro solder balls for BGA A vision system comprising a camera and LEDs is designed to capture the reflected images of multiple solder balls arranged arbitrarily on a tray and the locations of the LED point-light-source reflections in each ball are determined via image processing, for shape inspection. The proposed methodology aims to determine the presence of defects in 3D BGA shape using the statistical information of the relative positions of multiple BGA balls, which are included in the image. The presence of the BGA balls with large deviations in relative position imply the inconsistencies in their shape. Experiments were conducted to verify that the proposed method could be applied to inspection without sophisticated mechanism and productivity problem.

• The Journal of Korean Medicine
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• v.42 no.4
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• pp.208-221
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• 2021

Objectives: The purpose of this article was to investigate the current status of clinical studies of acupuncture treatment for depression using neuroimaging method, focusing on SCI papers. Methods: We searched for clinical trial studies of acupuncture treatment for depression using neuroimaging method in the MEDLINE (Pubmed), OASIS, and RISS database. Once the online search was finished, studies were selected manually by the inclusion criteria. Finally, we analyzed the characteristics of selected articles and reviewed the neural substrates of acupuncture treatment in depression. Results: Total eight studies were included in this study. The most frequently utilized modality was functional MRI. The most frequently selected acupoint for depression was GV20. Several studies revealed that acupuncture treatment could improve the symptoms of depression. In this manuscript, we demonstrated that neuroimaging techniques could capture the neural substrates associated with depression and acupuncture treatment may modulate the activation of brain areas which were impaired in depression in a different way from sham acupuncture. Conclusions: Utilizing neuroimaging methods to explore neural mechanism of acupuncture treatment on depression would be helpful in clinical trials and more efforts should be needed in this fields.

• Smart Media Journal
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• v.13 no.4
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• pp.9-15
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• 2024

Tree-based algorithms have been the dominant methods used build a prediction model for tabular data. This also includes personal credit data. However, they are limited to compatibility with categorical and numerical data only, and also do not capture information of the relationship between other features. In this work, we proposed an ensemble model using the Transformer architecture that includes text features and harness the self-attention mechanism to tackle the feature relationships limitation. We describe a text formatter module, that converts the original tabular data into sentence data that is fed into FinBERT along with other text features. Furthermore, we employed FT-Transformer that train with the original tabular data. We evaluate this multi-modal approach with two popular tree-based algorithms known as, Random Forest and Extreme Gradient Boosting, XGBoost and TabTransformer. Our proposed method shows superior Default Recall, F1 score and AUC results across two public data sets. Our results are significant for financial institutions to reduce the risk of financial loss regarding defaulters.

• Annual Conference of KIPS
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• 2024.10a
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• pp.636-639
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• 2024

Time series forecasting can be enhanced by integrating various data modalities beyond the past observations of the target time series. This paper introduces the Multimodal Block Transformer, a novel architecture that incorporates multivariate time series data alongside multimodal static information, which remains invariant over time, to improve forecasting accuracy. The core feature of this architecture is the Block Attention mechanism, designed to efficiently capture dependencies within multivariate time series by condensing multiple time series variables into a single unified sequence. This unified temporal representation is then fused with other modality embeddings to generate a non-autoregressive multi-horizon forecast. The model was evaluated on a dataset containing daily movie gross revenues and corresponding multimodal information about movies. Experimental results demonstrate that the Multimodal Block Transformer outperforms state-of-the-art models in both multivariate and multimodal time series forecasting.