• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.285-292
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• 2007

Magnetotelluric data recorded in the middle part of the Korean Peninsula are contaminated by severe noises at dead-band frequencies. In this study, we estimated the location of noise source using a source localization method. Since conventional beamforming techniques were not adequate for the localization of electromagnetic sources, we used the matched field processing and a genetic algorithm. The solutions for the strong noise signals tend to be localized in a narrow area, whereas those for natural MT signals shows randomly distributed patterns. The strong noise sources are mainly located in the western part of Kyonggi-do.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.255-261
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• 2020

We consider the problem of autonomously flying a quadcopter in indoor environments. Navigation in indoor settings poses two major issues. First, real time recognition of the marker captured by the camera. Second, The combination of the distributed images is used to determine the position and orientation of the quadcopter in an indoor environment. We autonomously fly a miniature RC quadcopter in small known environments using an on-board camera as the only sensor. We use an algorithm that combines data-driven image classification with image-combine techniques on the images captured by the camera to achieve real 3D localization and navigation.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.209-216
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• 2005

In wireless sensor networks, an estimation method is proposed for distances between nodes within two hops. The method uses only proximity information of nodes without physiccal distance measurements. It drastically improves the performance of localization algorithms based on Proximity information. In addition, it is the first method that estimates distances between nodes exactly in two hops. The distances are estimated from the number of common neighbors under an assumption that the number of common neighbors is proportional to the intersection of two unit disks centered at the two nodes. Simulation analysis shows that the estimation error is roughly from 10 to 20 percent of real distances. Meanwhile, the number of messages required by a distributed algorithm realizing this method is only two times the number of nodes.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1051-1058
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• 2011

Unmanned autonomous forklifts have a great potential to enhance the productivity of material handling in various applications because these forklifts can pick up and deliver loads without an operator and any fixed guide. Especially, automation of pallet loading and unloading technique is useful for enhancing performance of logistics and reducing cost for automation system. There are, however, many technical difficulties in developing such forklifts including localization, map building, sensor fusion, control, and so on. This is because the system requires numerous sensors, actuators, and controllers that need to be connected with each other, and the number of connections grows very rapidly as the number of devices grows. This paper presents a vision sensorbased autonomous loading and unloading for network-based unmanned forklift where system components are connected to a shared CAN network. Functions such as image processing and control algorithm are divided into small tasks that are distributed over a number of microcontrollers with a limited computing capacity. And the experimental results show that proposed architecture can be an appropriate choice for autonomous loading in the unmanned forklift.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.73-74
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• 2018

This paper presents the incorporation of still-alive access points (SAPs) and helper access points (HAPs) that can be utilized as anchor nodes for position estimation of a First Responders (FRs) for rapidly deployable Emergency Communication Systems (ECS) in disaster recovery. In addition, the localization environment has is formulated and initially examines the use of a distributed Gauss-Newton algorithm (GNA) as optimization technizue. A simulation has been conducted and compared with the commonly used trilateration approach in position estimation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.878-883
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• 2018

A jamming design scheme to disturb target position estimation of a bistatic multiple-input multiple-output(MIMO) radar system is presented. The proposed method exploits the received signals from distributed multiple electronic sensors and combines them to produce a jamming signal. The proposed algorithm can eliminate the target by transmitting the delayed sum or the weighted sum of the received senor signals. Simulation results confirm the performance of the proposed method.

• Smart Structures and Systems
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• v.24 no.2
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• pp.233-242
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• 2019

In this paper, an inverse approach based on uniform load surface (ULS) is presented for structural damage localization and quantification. The ULS is excellent approximation for deformed configuration of a structure under distributed unit force applied on all degrees of freedom. The ULS make use of natural frequencies and mode shapes of structure and in mathematical point of view is a weighted average of mode shapes. An objective function presented to damage detection is discrepancy between the ULS of monitored structure and numerical model of structure. Solving this objective function to find minimum value yields damage's parameters detection. The teaching-learning based optimization algorithm has been employed to solve inverse problem. The efficiency of present damage detection method is demonstrated through three numerical examples. By comparison between proposed objective function and another objective function which make use of natural frequencies and mode shapes, it is revealed present objective function have faster convergence and is more sensitive to damage. The method has good robustness against measurement noise and could detect damage by using the first few mode shapes. The results indicate that the proposed method is reliable technique to damage detection in structures.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.2
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• pp.31-38
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• 2007

To evaluate the accuracy and extent in the localization of cerebral motor coutex activation using a gradient- echo echo planar imaging(GE-EPI) compared to spin-echo echo planar iimaging(SE-EPI) on 3T MR imaging. Functional MR imaging of cerebral motor cortex activation was examined in GE-EPI and SE-EPI in five healthy male volunteers. A right finger movement was accomplished with a paradigm of 6 task and rest, periods and the cross-correlation was used for a statistical mapping algorithm. We evaluated any sorts of differenced of the time seried and the signal intensity changes between the rest and task periods obtained with two technoques. The qualitative analysis was distributed with activation sites of large veins and small veins by using two techniques and was found that both the techniques were clinically uesful for delineating large veins and small veins in fMRL Signal intensity charge of the rest and activation periods provided simmilar activations in both methods(GE-EPI : 0.93$\pm$0.11, SE-EPI : 0.80$\pm$.015) but the signal intensity in GE-EPI(133.95$\pm$15.76) was larger than in SE-EPI(74.5$\pm$18.90). The average SNRs of EPI raw data were higher at SMA in SE-EPI(48.54$\pm$12.37) than GE-EPI(41.4$\pm$12.54) and at M1 in SE-EPI(43.24$\pm$11.77) than GE-EPI(38.27$\pm$6.53). The localization of activation voxels of the GE-EPI showed a larger vein but the SE-EPI generally showed small vein. Then the analysis results of the two techniques were used for a statistacal paired student t-test. SE-EPI was found clinically useful for localizing the cerebral moter cortex cativation on 3.0T, but showed a little different activation patterns comparad to GE-EPI. In conclusion, SE-EPI may be feasible and can detect true cortical activation from capillaries and GE-EPI can obtain the large veins in the motor cortex activation on 3T MR imaging.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5445-5451
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• 2015

Fascin-1 (FSCN1) is an actin-bundling protein that induces cell membrane protrusions, increases cell motility, and is overexpressed in various human epithelial cancers, including esophageal squamous cell carcinoma (ESCC). We analyzed various protein-protein interactions (PPI) of differentially-expressed genes (DEGs), in fascin knockdown ESCC cells, to explore the role of fascin overexpression. The node-degree distributions indicated these PPI sub-networks to be characterized as scale-free. Subcellular localization analysis revealed DEGs to interact with other proteins directly or indirectly, distributed in multiple layers of extracellular membrane-cytoskeleton/ cytoplasm-nucleus. The functional annotation map revealed hundreds of significant gene ontology (GO) terms, especially those associated with cytoskeleton organization of FSCN1. The Random Walk with Restart algorithm was applied to identify the prioritizations of these DEGs when considering their relationship with FSCN1. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile following fascin knockdown to future examine the roles and mechanisms of fascin action.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.575-580
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• 2004

In this work, a method is presented to find an anatomical site of a current source crudely in a standard brain using grand average of MEG data. Minimum norm estimation algorithm and truncated singular value decomposition were applied to calculate the distributed sources that can reproduce the measured signals. Grand average over all subjects was obtained from the transformed signals, which would be detected in a standard sensor plane by the obtained distributed current sources. In the simulation study, it was shown that the localized dipole using the grand average is consistent with the mean location of localized dipoles of all subjects within several mm even with large inter-individual differences of sensor positions. This result suggests that the mean location of low level signal source can be estimated as a dipole source in grand average and it was confirmed in the localization of the current source of N100m. when the localized dipole is registered on a standard brain. This result also suggests that the activity region obtained from grand average can be crudely estimated on a standard brain using the source location of the N100m as a reference point.