• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.521-524
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• 2005

This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.324-332
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• 2010

The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings from heterogeneous sensors and subsequently detect complex events of interest in real-time fashion need further research. We are developing real-time event detection approaches which allow light-weight data fusion and do not require significant computing resources. Underlying the event detection framework is a collection of real-time monitoring and fusion mechanisms that are invoked upon the arrival of sensor data. The combination of these mechanisms and the framework has the potential to significantly improve the timeliness and reduce the resource requirements of embedded sensor networks. In addition to that, we discuss about a privacy that is foundation technique for trusted embedded sensor network system and explain anonymization technique to ensure privacy.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.123-130
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• 2007

The aim of this study was to propose a fusion and registration method with heterogeneous small animal acquisition system in small animal in-vivo study. After an intravenous injection of $^{18}F$-FDG through tail vain and 60 min delay for uptake, mouse was placed on an acryl plate with fiducial markers that were made for fusion between small animal PET (microPET R4, Concorde Microsystems, Knoxville TN) and Discovery LS CT images. The acquired emission list-mode data was sorted to temporally framed sinograms and reconstructed using FORE rebining and 2D-OSEM algorithms without correction of attenuation and scatter. After PET imaging, CT images were acquired by mean of a clinical PET/CT with high-resolution mode. The microPET and CT images were fusion and co-registered using the fiducial markers and segmented lung region in both data sets to perform a point-based rigid co-registration. This method improves the quantitative accuracy and interpretation of the tracer.

• Smart Structures and Systems
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• v.31 no.3
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• pp.275-281
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• 2023

In recent years, technological developments have rapidly increased the number of complex structures and equipment in the industrial. Accordingly, the prognostics and health monitoring (PHM) technology has become significant. The safety assessment of industrial sites requires data obtained by installing a number of sensors in the structure. Therefore, digital twin technology, which forms the core of the Fourth Industrial Revolution, is attracting attention in the safety field. The research on digital twin technology of structures subjected to seismic loads has been conducted recently. Hence, this study proposes a digital twin system that estimates the responses and arbitrary load in real time by utilizing the minimum sensor to a pipe that receives a seismic and arbitrary load. To construct the digital twin system, a finite-element model was created considering the dynamic characteristics of the pipe system, and then updating the finite-element model. In addition, the calculation speed was improved using a finite-element model that applied the reduced-order modeling (ROM) technology to achieve real-time performance. The constructed digital twin system successfully and rapidly estimated the load and the point where the sensor was not attached. The accuracy of the constructed digital twin system was verified by comparing the response of the digital twin model with that derived by using the load estimated from the digital twin model as input in the finite-element model.

• ETRI Journal
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• v.33 no.4
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• pp.506-516
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• 2011

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1516-1529
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• 2023

In this paper, a motor gearbox fault-detection system based on a hierarchical flow-based model is proposed. The proposed system is used for the anomaly detection of a motion sound-based actuator module. The proposed flow-based model, which is a generative model, learns by directly modeling a data distribution function. As the objective function is the maximum likelihood value of the input data, the training is stable and simple to use for anomaly detection. The operation sound of a car's side-view mirror motor is converted into a Mel-spectrogram image, consisting of a folding signal and an unfolding signal, and used as training data in this experiment. The proposed system is composed of an encoder and a decoder. The data extracted from the layer of the pretrained feature extractor are used as the decoder input data in the encoder. This information is used in the decoder by performing an interlayer cross-scale convolution operation. The experimental results indicate that the context information of various dimensions extracted from the interlayer hierarchical data improves the defect detection accuracy. This paper is notable because it uses acoustic data and a normalizing flow model to detect outliers based on the features of experimental data.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.139-148
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• 2015

The purpose of image fusion is to combine the relevant information from a set of images into a single image, where the resultant fused image will be more informative and complete than any of the input images. Image fusion techniques can improve the quality and increase the application of these data important applications of the fusion of images include medical imaging, remote sensing, and robotics. In this paper, we suggest a new method to generate a fusion image using the close relation of image features obtained through maximum entropy threshold and mutual information. This method represents a good image registration in case of using a blurring image than other image fusion methods.

• The Korean Journal of Physiology and Pharmacology
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• v.7 no.6
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• pp.375-379
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• 2003

$Ca^{2+}$ influx appears to be important for triggering myoblast fusion. It remains, however, unclear how $Ca^{2+}$ influx rises prior to myoblast fusion. Recently, several studies suggested that NMDA receptors may be involved in $Ca^{2+}$ mobilization of muscle, and that $Ca^{2+}$ influx is mediated by NMDA receptors in C2C12 myoblasts. Here, we report that other types of ionotropic glutamate receptors, non-NMDA receptors (AMPA and KA receptors), are also involved in $Ca^{2+}$ influx in myoblasts. To explore which subtypes of non-NMDA receptors are expressed in C2C12 myogenic cells, RT-PCR was performed, and the results revealed that KA receptor subunits were expressed in both myoblasts and myotubes. However, AMPA receptor was not detected in myoblasts but expressed in myotubes. Using a $Ca^{2+}$ imaging system, $Ca^{2+}$ influx mediated by these receptors was directly measured in a single myoblast cell. Intracellular $Ca^{2+}$ level was increased by KA, but not by AMPA. These results were consistent with RT-PCR data. In addition, KA-induced intracellular $Ca^{2+}$ increase was completely suppressed by treatment of nifedifine, a L-type $Ca^{2+}$ channel blocker. Furthermore, KA stimulated myoblast fusion in a dose-dependent manner. CNQX inhibited not only KA-induced myoblast fusion but also spontaneous myoblast fusion. Therefore, these results suggest that KA receptors are involved in intracellular $Ca^{2+}$ increase in myoblasts and then may play an important role in myoblast fusion.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.371-379
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• 2018

Unlike general VHR (Very-High-Resolution) satellite sensors that are mainly for panchromatic and MS (Multispectral) imaging, Worldview-3 sensor additionally provides eight SWIR (Short Wavelength Infrared) bands in wavelength range from 1198 nm to 2365 nm. This study investigates the effect of informative Worldview-3 SWIR bands for wetland classification performance. Worldview-3 imagery acquired over Sunchon Bay, which is a coastal wetland located in South Korea, is used to implement the classification. Land-cover classes for the scene are determined by referring to national land-cover maps, which are provided by the Ministry of Environment, overlapped with the scene. After that, training data for each determined class are collected. In order to analyze the effect of SWIR bands, classifications with and without SWIR bands are carried out and the results are then compared. In this regard, a SVM (Support Vector Machine) is utilized as their classifier. As a result of the accuracy assessments performed by test data that are independently extracted from training data, it was confirmed that classification performance was improved when the SWIR bands are included as input features for SVM-based classification.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06b
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• pp.437-440
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• 2007

최근 환경 문제를 해결하기 위하여 환경 문제의 많은 컴퓨터 기술들이 응용되고 있다. 환경 정보는 환경오염원 및 주위에 미치는 영향과 오염된 농도에 대한 정보를 연구 및 분석 할 수 있는 분야이다. 최근 환경에 관련 연구가 일부에서 수행되고 있으나 이를 IT기술과 접목하여 다양한 정보를 효율적으로 저장 및 검색 할 수 있는 시스템은 부족한 실정이다. 또한 현재 환경오염의 측정방법으로는 수작업으로 이루어지는 경우가 많아서 공간적 및 물리적 제약이 있는 따르는 실정이다. 환경오염에 관한 정보를 센서를 사용하여 사용자에게 실시간으로 효과적으로 저장 관리하여 관련된 연구자들 간에 서로가 필요한 정보를 쉽게 공유할 수 있도록 본 논문에서는 Ubiquitous Sensor Network(USN), Java Message Service(JMS) 및 Webservice를 이용한 환경 모니터링 서비스를 제안 한다. 본 논문에서 제안한 시스템은 환경정보와 사용자간에 유연성, 확장성 및 실시간을 보장해 주는 시스템을 구현한다.