• Biomaterials and Biomechanics in Bioengineering
• /
• v.3 no.3
• /
• pp.129-140
• /
• 2016

This article reports the development of biodegradable photoluminescent polymer (BPLP)-based nanoparticles (NPs) incorporating either magnetic nanoparticles (BPLP-MNPs) or gadopentate dimeglumine (BPLP-Gd NPs), for cancer diagnosis and treatment. The aim of the study is to compare these nanoparticles in terms of their surface properties, fluorescence intensities, MR imaging capabilities, and in vitro characteristics to choose the most promising dual-imaging nanoprobe. Results indicate that BPLP-MNPs and BPLP-Gd NPs had a size of $195{\pm}43nm$ and $161{\pm}55nm$, respectively and showed good stability in DI water and 10% serum for 5 days. BPLP-Gd NPs showed similar fluorescence as the original BPLP materials under UV light, whereas BPLP-MNPs showed comparatively less fluorescence. VSM and MRI confirmed that the NPs retained their magnetic properties following encapsulation within BPLP. Further, in vitro studies using HPV-7 immortalized prostate epithelial cells and human dermal fibroblasts (HDFs) showed > 70% cell viability up to $100{\mu}g/ml$ NP concentration. Dose-dependent uptake of both types of NPs by PC3 and LNCaP prostate cancer cells was also observed. Thus, our results indicate that BPLP-Gd NPs would be more appropriate for use as a dual-imaging probe as the contrast agent does not mask the fluorescence of the polymer. Future studies would involve in vivo imaging following administration of BPLP-Gd NPs for biomedical applications including cancer detection.

• The Journal of Korean Association of Computer Education
• /
• v.13 no.4
• /
• pp.77-86
• /
• 2010

In this paper, we propose a real time post-processing visual enhancement technique to reduce the blocking artifacts in block based DCT decoded image for mobile devices that have allocation of the restricted resource. In order to reduce the blocking artifacts effectively even while preserving the image edge to the utmost, the proposed algorithm uses the deblocking filtering or the directional filtering according to the edge detection of the each pixel. After it is discriminated that the pixel to apply the deblocking filtering belongs again to the monotonous area, the weighted average filter with the adaptive mask is applied for the pixel to remove the blocking artifacts. On the other hand, a new directional filter is utilized to get rid of staircase noise and preserve the original edge component. Experimental results show that the proposed algorithm produces better results than those of the conventional algorithms in both subjective and objective qualities.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.11
• /
• pp.365-368
• /
• 1997

We are developing a small gamma camera or imaging malignant breast tumors. The small scintillation camera system consists of NaI(Tl) crystal ($60\;{\times}\;60\;{\times}\;6\;mm^3$) coupled to position sensitive photomultiplier tube (PSPMT), nuclear instrument module (NIM), analog to digital converter (ADC), and personal computer. High quality flood source image and hole mask image were obtained using the gamma camera developed in this study. Breast phantom containing $2{\sim}7\;mm$ diameter spheres was successfully imaged with parallel hole collimator. The obtained image displayed accurate activity distribution over the imaging field of view. Linearity and uniformity correction algorithms are being developed. It is believed that the developed small gamma camera could be useful or detection of malignant breast cancer.

• Journal of Trauma and Injury
• /
• v.31 no.2
• /
• pp.103-106
• /
• 2018

Fat embolism refers to the presence of fat droplets within the peripheral and lung microcirculation with or without clinical sequelae. However, early diagnosis of fat embolism is very difficult because the embolism usually does not show at the computed tomography as a large fat complex within vessels. Forty-eight-year-old male with pedestrian traffic accident ransferred from a local hospital by helicopter to the regional trauma center by two flight surgeons on board. At the rendezvous point, he had suffered with dyspnea without any airway obstruction sign with 90% of oxygen saturation from pulse oximetry with giving 15 L of oxygen by a reserve bag mask. The patient was intubated at the rendezvous point. The secondary survey of the patient revealed multiple pelvic bone fracture with sacrum fracture, right femur shaft fracture and right tibia head fracture. Abdominal computed tomography was performed in 191 minutes after the injury and fat embolism with Hounsfield unit of -86 in his right common iliac vein was identified. Here is a very rare case that mass of fat embolism was shown within common iliac vein detected in computed tomography. Early detection of the fat embolus and early stabilization of the fractures are essential to the prevention of sequelae such as cerebral fat embolism.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.10A
• /
• pp.1546-1554
• /
• 1999

In this paper, Dynamic Fault Tree algorithm(DFT algorithm) is presented. This algorithm provides a concise representation of dynamic fault tolerance system including fault recovery techniques with fault detection, mask and switching function. And this algorithm define FDEP, CSP, SEQ, PAG gate which captures the dynamic characteristics of system. It show that this algorithm solved the constraints to satisfy the dynamic characteristics of system which there are in Markov and also this is able to satisfy the dynamic characteristics of system which there are in Markov and also this is able to covered the disadvantage of Fault tree methods. To show the key advantage of this algorithm, a traditional method, that is, Markov and Fault Tree, applies to TMR and Dual-Duplex systems with the dynamic characteristic and a presented method applies to those. He results proved that the DFT algorithm for solving the problems of the system is more effective than the Markov and Fault tree analysis model..

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.5
• /
• pp.275-280
• /
• 2013

In this paper, a new stereo object extraction algorithm using a block-based MSE (mean square error) algorithm and the configuration parameters of a stereo camera is proposed. That is, by applying the SSD algorithm between the initial reference image and the next stereo input image, location coordinates of a target object in the right and left images are acquired and then with these values, the pan/tilt system is controlled. And using the moving angle of this pan/tilt system and the configulation parameters of the stereo camera system, the mask window size of a target object is adaptively determined. The newly segmented target image is used as a reference image in the next stage and it is automatically updated in the course of target tracking basing on the same procedure. Meanwhile, a target object is under tracking through continuously controlling the convergence and FOV by using the sequentiall extracted location coordinates of a moving target.

• Journal of Electrochemical Science and Technology
• /
• v.8 no.1
• /
• pp.43-52
• /
• 2017

In this paper, for the first time, the electroanalytical study of Triethylenediamine, TEDA was done on a typically graphene modified carbon paste electrode (Gr/CPE) in pH=10.5 of phosphate buffer solutions (PBS). The surface morphology of the bare and modified electrodes was characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The electro-oxidation of TEDA was investigated at the surface of modified electrode. The results revealed that the oxidation peak current of TEDA at the surface of Gr/CPE is 2.70 times than that shown at bare-CPE. A linear calibration plot was observed in the range of 1.0 to 202.0 ppm. In this way, the detection limit was found to be 0.18 ppm. The method was then successfully applied to determination of TEDA in aqueous samples obtained from two kinds of activated carbon from the masks of war. On the other hand, density functional theory (DFT) method at B3LYP/6-311++G** level of theory and a conductor-like Polarizable Continuum Model (CPCM) was used to calculate the $pK_a$ values of TEDA. The energies of lowest unoccupied molecular orbital ($E_{LUMO}$) and highest occupied molecular orbital ($E_{HOMO}$), gap energy (${\Delta}E$) and some thermodynamic parameters such as Gibbs free energy of TEDA and its conjugate acid ($HT^+$) were calculated. The results of calculated $pK_a$ were found to be in good agreement with the experimental values.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.1
• /
• pp.111-118
• /
• 2022

In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

• Atmosphere
• /
• v.31 no.5
• /
• pp.489-510
• /
• 2021

In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.701-720
• /
• 2023

Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.