• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.163-170
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• 1998

The ultimate goal of total artificial heart is permanent substitute for a failed heart in a patient without any other therapeutic modality. Until now, infection has been the main problem related to the mechanical circulatory support system. The best way to solve this catastrophic complication and to improve the quality of life of TAH patients in terms of tethering must be implantation of TAH totally. The EH-TAH has been developed in NCVC from 1987 for this purpose. The system consists of an energy converter and pumps, which are designed to be placed in abdomen and pericardial space separately for a good anatomical fit. To evaluate the anatomical fit and hemodynamic performance of the EH-TAH, in vivo test was done. General condition of the animal and hemodynamic status had been stable until the TAH stopped on the 11th pumping day. The estimated cardiac output was about 7.7L/min. The values of mean aortic pressure, left and right atrial pressure were 93$\pm$10, 19$\pm$3 and 15$\pm$4 mmHg, respectively. The correlation coefficient between left and right atrial pressure was 0.96, which represents the dynamic function of the interatrial shunt in controlling left-right imbalance of cardiac output. During pumping days, the temperature on the surface of actuator had been maintained at 39.7$\pm$0.4$^{\circ}C$, less than 1$^{\circ}C$ higher than the rectal temperature. The TAH stopped on the 11th day due to mechanical problems. We concluded that the EH-TAH possessed satisfactory basic performance including anatomic fit and hemodynamic adequacy, although there were several mechanical problems to be solved yet.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.297-304
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• 2004

In this paper, a mesh simplification algorithm based on wavelet transform and 2D planar sampling is proposed for efficient handling of 3D objects in computer applications. Since 3D vertices are directly transformed with wavelets in conventional mesh compression and simplification algorithms, it is difficult to solve tiling optimization problems which reconnect vertices into faces in the synthesis stage highly demanding vertex connectivities. However, a 3D mesh is sampled onto 2D planes and 2D polygons on the planes are independently simplified in the proposed algorithm. Accordingly, the transform of 2D polygons is very tractable and their connection information Is replaced with a sequence of vertices. The vertex sequence of the 2D polygons on each plane is analyzed with wavelets and the transformed data are simplified by removing small wavelet coefficients which are not dominant in the subjective quality of its shape. Therefore, the proposed algorithm is able to change the mesh level-of-detail simply by controlling the distance of 2D sampling planes and the selective removal of wavelet coefficients. Experimental results show that the proposed algorithm is a simple and efficient simplification technique with less external distortion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.502-507
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• 2016

Vanadium dioxide, $VO_2$, is a thermochromic material that exhibits a reversible metal-insulator phase transition at $68^{\circ}C$, which accompanies rapid changes in the optical and electronic properties. To decrease the transition temperature around room temperature, a number of studies have been performed. The phase transition temperature of 1D nanowire $VO_2$ with a 100 nm diameter was reported to be approximately $29^{\circ}C$. In this study, 1D or 2D nanostructured $VO_2$ was grown using the vapor transport method. Vanadium dioxide has a different morphology with the same growth conditions for different substrates. The 1D nanowires $VO_2$ were grown on a Si substrate ($Si{\setminus}SiO_2$(300 nm), whereas the 2D & 3D nanostructured $VO_2$ were grown on an exfoliated graphene nanosheet. The crystallographic properties of the 1D or 2D & 3D nanostructured $VO_2$, which were grown by thermal CVD, and exfoliated-transferred graphene nanosheets on a Si wafer which was used as substrate for the vanadium oxide nanostructures, were analyzed by Raman spectroscopy. The as-grown vanadium oxide nanostructures have a $VO_2$ phase, which are confirmed by Raman spectroscopy.

• Journal of Science and Technology Studies
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• v.15 no.2
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• pp.229-262
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• 2015

Toxic tort cases have increased dramatically since the 1970s, as large technological systems, such as nuclear power plants and chemical factories, or mass-produced, high-tech products, had exposed citizens and consumers to dangerous substances. It was, however, difficult to establish causal connection between exposure and the alleged harms in many of the environmental, pollution, and product liability cases under the framework of tort law conception of causation and responsibility. Science and law was called upon to resolve such 'late modern' legal cases where true causes are hard to find, where no single explanatory factor is sufficient for explaining diseases like cancer. This article examines how plaintiffs in the Korean tobacco litigation mobilized such late modern tools in science and law, such as epidemiology and the allocation of the burden of proof, in the context of the global circulation of science and law. It further shows how a set of the scientific theories and legal arguments developed in order to cope with late modern risk played a central role in establishing a causation between smoking and cancer in 2011. This article suggests that STS scholars can fruitfully examine the interaction between science and law as a way to understand and engage with social and legal issues engendered by late modern risk.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.121-133
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• 2005

Texture imaging, which means texture image creation by co-occurrence relation, has been known as one of the useful image analysis methodologies. For this purpose, most commercial remote sensing software provides texture analysis function named GLCM (Grey Level Co-occurrence Matrix). In this study, texture-imaging program based on GLCM algorithm is newly implemented. As well, texture imaging modules for GLDV (Grey Level Difference Vector) are contained in this program. As for GLCM/GLDV Texture imaging parameters, it composed of six types of second order texture functions such as Homogeneity, Dissimilarity, Energy, Entropy, Angular Second Moment, and Contrast. As for co-occurrence directionality in GLCM/GLDV, two direction modes such as Omni-mode and Circular mode newly implemented in this program are provided with basic eight-direction mode. Omni-mode is to compute all direction to avoid directionality complexity in the practical level, and circular direction is to compute texture parameters by circular direction surrounding a target pixel in a kernel. At the second phase of this study, some case studies with artificial image and actual satellite imagery are carried out to analyze texture images in different parameters and modes by correlation matrix analysis. It is concluded that selection of texture parameters and modes is the critical issues in an application based on texture image fusion.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.234-240
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• 2021

In this paper, the mask-based speech enhancement is improved for effective speech recognition in noise environments. In the mask-based speech enhancement, enhanced spectrum is obtained by multiplying the noisy speech spectrum by the mask. The VoiceFilter (VF) model is used as the mask estimation, and the Spectrogram Inpainting (SI) technique is used to remove residual noise of enhanced spectrum. In this paper, we propose a combined loss to further improve speech enhancement. In order to effectively remove the residual noise in the speech, the positive part of the Triplet loss is used with the component loss. For the experiment TIMIT database is re-constructed using NOISEX92 noise and background music samples with various Signal to Noise Ratio (SNR) conditions. Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligibility (STOI) are used as the metrics of performance evaluation. When the VF was trained with the mean squared error and the SI model was trained with the combined loss, SDR, PESQ, and STOI were improved by 0.5, 0.06, and 0.002 respectively compared to the system trained only with the mean squared error.

• Journal of Life Science
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• v.29 no.6
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• pp.712-723
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• 2019

Chemically synthesized compounds are widely used in oral hygiene products. However, excessively long-term use of these chemicals can cause undesirable side effects such as bacterial tolerance, allergy, and tooth discoloration. To solve these issues, significant effort is put into the search for natural antibacterial agents. The aim of this study was to assess the extracts of foreign native plants that inhibit the growth and biofilm formation of Streptococcus mutans. Among the 300 foreign plant extracts used in this study, Chesneya nubigena (D. Don) Ali extract had the highest antimicrobial activity relatively against S. mutans with a clear zone of 9 mm when compared to others. This plant extract also showed anti-biofilm activity and bacteriostatic effect (minimal bactericidal concentration [MBC], 1.5 mg/ml). In addition, the plant extracts of 19 species decreased the ability of S. mutans to form biofilm at least a 6-fold in proportion to the tested concentrations. Of particular note, C. nubigena (D. Don) Ali extract was found to inhibit biofilm formation at the lowest concentration tested effectively. Therefore, our results reveal that C. nubigena (D. Don) Ali extract is a potential candidate for the development of antimicrobial substitutes, which might be effective for caries control as well, as demonstrated by its inhibitory effect on the persistence and pathogenesis of S. mutans.

• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.290-296
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• 2021

The effect of draw ratio (8, 10, 12, 14 times) and additive CaCO₃ content (0, 0.5, 1.0, 1.5, 2.0, and 3.0 wt%) on the properties of high-performance PE monofilament was investigated in this study. As the draw ratio increased (8-14 times), the melting enthalpy (ΔHf), crystallinity, specific gravity, and tensile strength increased significantly. However, the draw ratio had little effect on the melting temperature (Tm) and crystallization temperature (Tc). The seawater fastness (stain and fade) of the hydrophobic PE monofilament prepared in this study showed an excellent grade of 4-5 in all draw ratios. To investigate the effect of the additive CaCO₃ content on the properties of high-performance PE monofilament, the draw ratio was fixed at 14 times. It was found that the tensile strength of the PE monofilament sample containing 0.5 wt% of CaCO₃ was much greater compared to the sample without CaCO₃, but the elongation of the sample containing 0.5 wt% of CaCO₃ was much less than the sample with 0 wt% CaCO₃. However, in the case of the sample containing more than 0.5 wt% CaCO₃, the tensile strength slightly decreased and the elongation slightly increased as the CaCO₃ content increased. The seawater fastness (stain and fade) of the hydrophobic PE monofilament showed excellent grades of 4-5, regardless of the amount of additives. From the above results, it was found that the maximum draw ratio of 14 times with an additive of 0.5 wt% CaCO₃ are the optimal conditions for manufacturing high-performance marine fusion materials with various fineness (denier) with high strength and low elongation.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.365-379
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• 2021

Hydrological model parameters are essential for model simulation and can vary over time due to topography, climatic conditions, climate change and human activity. Consequently, the use of fixed parameters can lead to inaccurate stream flow simulations. The aim of this study is to investigate an appropriate method of estimating time-varying parameters using stream flow observations, and how the simulation efficiency changes when stream flow data are assimilated into the model. The data assimilation method can be used to automatically estimate the parameters of a hydrological model by adapting to a variety of changing environments. Stream flow observations were assimilated into a two parameter monthly water balance model using a particle filter. The simulation results using the time-varying parameters by the data assimilation method were compared with the simulation results using the fixed parameters by the SCEM method. First, we conducted synthesis experiments based on various scenarios to investigate if the particle filter method can adequately track parameters that change over time. After that, it was applied to actual watersheds and compared with the predictive performance of stream flow when using parameters that change with time and fixed parameters. The conclusions obtained through this study are as follows: (1) The predictive performance of the overall monthly stream flow time series was similar between the particle filter method and the SCEM method. (2) The monthly runoff prediction performance in the period except the rainy season was better in the simulation by the periodically changing parameters using the data assimilation method. (3) Uncertainty in the observational data of stream flow used for assimilation played an important role in the predictive performance of the particle filter.