• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.188-196
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• 2013

We have investigated the effects of formalin on the assembly of colloidal gold nanoparticles (AuNPs) prepared by laser ablation of a solid gold target in deionized water. Upon addition of formalin, the surface plasmon resonance (SPR) band at 519 nm for pure AuNPs decreases and shifts to red while a new broad SPR band appears at ~700 nm. The red-shift is prominent with increase in the incubation time. The average size of the initial AuNPs is around 12 nm but it increases to 23 nm after addition of formalin. It turns out that formalin acts as a cationic surfactant for AuNPs with negative surface charge in the colloidal solutions. Furthermore, through analysis of the Raman spectrum of formalin and the density functional theory calculations, we confirm that methanediol is the main species in formalin which is in charge of the aggregation of AuNPs.

• BMB Reports
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• v.41 no.12
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• pp.852-857
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• 2008

Little attention has been paid to the specificity between E2 and the target protein during ubiquitination, although RING-E3 induces a potential intra-molecular reaction by mediating the direct transfer of ubiquitin from E2 to the target protein. We have constructed artificial E2 fusion proteins in which a target protein (p27) is tethered to one of six E2s via a flexible linker. Interestingly, only three E2s (UbcH5b, hHR6b, and Cdc34) are able to ubiquitinate p27 via an intra-molecular reaction in this system. Although the first ubiquitination of p27 (p27-Ub) by Cdc34 is less efficient than that of UbcH5b and hHR6b, the additional ubiquitin attachment to p27-Ub by Cdc34 is highly efficient. The E2 core of Cdc34 provides specificity to p27, and the residues 184-196 are required for possessive ubiquitination by Cdc34. We demonstrate direct E2 specificity for p27 and also show that differential ubiquitin linkages can be dependent on E2 alone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2605-2625
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• 2024

Siamese-based segmentation and tracking algorithms improve accuracy and stability for video object segmentation and tracking tasks simultaneously. Although effective, variability in target appearance and background clutter can still affect segmentation accuracy and further influence the performance of tracking. In this paper, we present a memory propagation-based target-aware and mask-attention decision network for robust object segmentation and tracking. Firstly, a mask propagation-based attention module (MPAM) is constructed to explore the inherent correlation among image frames, which can mine mask information of the historical frames. By retrieving a memory bank (MB) that stores features and binary masks of historical frames, target attention maps are generated to highlight the target region on backbone features, thus suppressing the adverse effects of background clutter. Secondly, an attention refinement pathway (ARP) is designed to further refine the segmentation profile in the process of mask generation. A lightweight attention mechanism is introduced to calculate the weight of low-level features, paying more attention to low-level features sensitive to edge detail so as to obtain segmentation results. Finally, a mask fusion mechanism (MFM) is proposed to enhance the accuracy of the mask. By utilizing a mask quality assessment decision network, the corresponding quality scores of the "initial mask" and the "previous mask" can be obtained adaptively, thus achieving the assignment of weights and the fusion of masks. Therefore, the final mask enjoys higher accuracy and stability. Experimental results on multiple benchmarks demonstrate that our algorithm performs outstanding performance in a variety of challenging tracking tasks.

• Progress in Medical Physics
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• v.21 no.4
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• pp.354-359
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• 2010

The purpose of this study is to verify the dosimetric effect on real PTV (planning target volume) coverage and safety of OARs (organs at risk) at various image fusion protocol-based radiosurgery plan for pituitary adenomas. Real PTV coverage and its variation was acquired and maximum dose and the volume absorbing above threshold dose were also measured for verifying the safety of optic pathway and brainstem. The protocol that can reduce superior-inferior uncertainty by using both axial and coronal MR (magnetic resonance) image sets shows relatively lower values than that of case using only axial image sets. As a result, the image fusion protocol with both axial and coronal image sets can be beneficial to generate OAR-weighted radiosurgery plan.

• Molecular & Cellular Toxicology
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• v.4 no.1
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• pp.78-84
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• 2008

EGFR has been intensively investigated as a target to block the signal transduction pathway which stimulates cancer growth and metastasis. Studies about structure-activity relationship for tricyclic azepine derivatives were performed with topomer-CoMFA. The derived topomer-CoMFA model with steric and electrostatic field parameters based on fragment units gave reasonable statistics ($q^2$=0.561, $r^2$=0.679). The model explains why a halogen atom at the meta position of aniline is important to increases inhibitory activity. This comes from an electrostatically negative groups are favored near this region. The model also shows that there are sterically favored regions around methoxy group extended from oxazepine derivatives. The findings about steric and electrostatic effects can be utilized for designing new inhibitors.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.523-530
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• 2019

The purpose of this study was to obtain the K-edge images using a spectral CT system based on a photon-counting detector and implement the 3D fusion imaging using the conventional and spectral CT images. Also, we evaluated the clinical feasibility of the 3D fusion images though the quantitative analysis of image quality. A spectral CT system based on a CdTe photon-counting detector was used to obtain K-edge images. A pork phantom was manufactured with the six tubes including diluted iodine and gadolinium solutions. The K-edge images were obtained by the low-energy thresholds of 35 and 52 keV for iodine and gadolinium imaging with the X-ray spectrum, which was generated at a tube voltage of 100 kVp with a tube current of $500{\mu}A$. We implemented 3D fusion imaging by combining the iodine and gadolinium K-edge images with the conventional CT images. The results showed that the CNRs of the 3D fusion images were 6.76-14.9 times higher than those of the conventional CT images. Also, the 3D fusion images was able to provide the maps of target materials. Therefore, the technique proposed in this study can improve the quality of CT images and the diagnostic efficiency through the additional information of target materials.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.22-28
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• 1992

The need for intelligent systems that can operate in an unstructured, dynamic environment has created a growing demand for the use of multiple, distributed sensors. While most research in multisensor fusion has revolved around applications in object recognition-including military applications for automatic target recognition-developments in microsensor technology are encouraging more research in affordable, highly-redundant sensor networks. Three trends that are described at length are the increasing use of microsensors, the techniques that are used in the handling of partial or uncertain data, and the application of neural network techniques for sensor fusion.

• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.556-561
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• 2011

It is generally known that particle filters can produce consistent target tracking performance in comparison to the Kalman filter for non-linear and non-Gaussian systems. In this paper, I propose a Rao-Blackwellized multiple model particle filter(RBMMPF) to enhance computational efficiency of the particle filters as well as to reduce sensitivity of modeling. Despite that the Rao-Blackwellized particle filter needs less particles than general particle filter, it has a similar tracking performance with a less computational load. Comparison results for performance is listed for the using single sensor information RBMMPF and using multisensor data fusion RBMMPF.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.764-776
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• 1999

In this paper, a tracking algorithm for a maneuvering single target in the presence of multiple data from multiple sensors is investigated. Allowing individual sensors to function by themselves, the estimates from individual sensors on the same target are fused for the purpose of improving the state estimate. The filtering method adopted in the local sensors is the variable dimensional filter with input estimatio technique, which consists of a constant velocity model and a constant acceleration model. A posteriori probability for the maneuvering hypothesis is newly derived. It is shown that the relation function of the a posteriori probability is a function of only the covariance of the fused estimates. Simulation results are provided.