• 한국연소학회:학술대회논문집
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• 2005.10a
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• pp.58-63
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• 2005

As fuel cells approach commercialization, hydrogen production becomes a critical step in the overall energy conversion pathway. Reforming is a process that produces a hydrogen-rich gas from hydrocarbon fuels. Hydrogen production via autothermal reforming (ATR) is particularly attractive for applications that demand a quick start-up and response time in a compact size. However, further research is required to optimize the performance of autothermal reformers and accurate models of reactor performance must be developed and validated. The design includes the requirement of accommodating a wide range of experimental set ups. Factors considered in the design of the reformer are capability to use multiple fuels, ability to vary stoichiometry, precise temperature and pressure control, implementation of enhancement methods, capability to implement variable catalyst positions and catalyst arrangement, ability to monitor and change reactant mixing, and proper implementation of data acquisition. A model of the system was first developed in order to calculate flowrates, heating, space velocity, and other important parameters needed to select the hardware that comprises the reformer. Predicted performance will be compared to actual data once the reformer construction is completed. This comparison will quantify the accuracy of the model and should point to areas where further model development is required. The end result will be a research tool that allows engineers to optimize hydrogen production via autothermal reformation.

• Journal of Mechanical Science and Technology
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• v.20 no.6
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• pp.864-873
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• 2006

As fuel cells approach commercialization, hydrogen production becomes a critical step in the overall energy conversion pathway. Reforming is a process that produces a hydrogen-rich gas from hydrocarbon fuels. Hydrogen production via autothermal reforming (ATR) is particularly attractive for applications that demand a quick start-up and response time in a compact size. However, further research is required to optimize the performance of autothermal reformers and accurate models of reactor performance must be developed and validated. The design includes the requirement of accommodating a wide range of experimental set ups. Factors considered in the design of the reformer are capability to use multiple fuels, ability to vary stoichiometry, precise temperature and pressure control, implementation of enhancement methods, capability to implement variable catalyst positions and catalyst arrangement, ability to monitor and change reactant mixing, and proper implementation of data acquisition. A model of the system was first developed in order to calculate flowrates, heating, space velocity, and other important parameters needed to select the hardware that comprises the reformer. Predicted performance will be compared to actual data once the reformer construction is completed. This comparison will quantify the accuracy of the model and should point to areas where further model development is required. The end result will be a research tool that allows engineers to optimize hydrogen production via autothermal reformation.

• Natural Product Sciences
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• v.27 no.4
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• pp.264-273
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• 2021

Simultaneous quantification of multiple marker compounds in herbal medicine by high performance liquid chromatography (HPLC) analysis is still a challenge due to the complexity in various parameters to be considered and co-existing multi-components. As a case study, a reliable HPLC method for simultaneous quantification of paeoniflorin from Paeoniae Radix and decursin from Angelicae Gigantis Radix in various commercial herbal medicine was developed based on analytical quality by design (AQbD) strategy. As a first step, risk assessment was performed to select the critical method parameters (CMPs) which were decided as organic mobile phase ratio and column oven temperature. In order to evaluate the effect of the CMPs on critical method attributes (CMAs) of peak resolution and tailing, central composite design (CCD) was employed. The final chromatographic conditions were optimized as follows: column- C₁₈, 4.6 × 250 mm, 5 ㎛ particle size; mobile phase- A: acetonitrile, B: 0.1% acetic acid water; detection wavelength- 235 nm for paeoniflorin, 325 nm for decursin; column oven temperature- 25℃; flow rate- 1.0 mL/min; gradient mobile phase system as Time (min) : % A, 0:14, 25:14, 30:50, 60:50, 61:100, 65:100, 66:14, 75:14. The method was successfully validated according to the International Conference on Harmonization (ICH) guidelines and piloted for ten commercial herbal medicines.

• Parasites, Hosts and Diseases
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• v.60 no.4
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• pp.295-299
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• 2022

Malaria elimination and control require prompt and accurate diagnosis for treatment plan. Since microscopy and rapid diagnostic test (RDT) are not sensitive particularly for diagnosing low parasitemia, highly sensitive diagnostic tools are required for accurate treatment. Molecular diagnosis of malaria is commonly carried out by nested polymerase chain reaction (PCR) targeting 18S rRNA gene, while this technique involves long turnaround time and multiple steps leading to false positive results. To overcome these drawbacks, we compared highly sensitive cytochrome oxidase gene-based single-step multiplex reaction with 18S rRNA nested PCR. Cytochrome oxidase (cox) genes of P. falciparum (cox-III) and P. vivax (cox-I) were compared with 18S rRNA gene nested PCR and microscopy. Cox gene multiplex PCR was found to be highly specific and sensitive, enhancing the detection limit of mixed infections. Cox gene multiplex PCR showed a sensitivity of 100% and a specificity of 97%. This approach can be used as an alternative diagnostic method as it offers higher diagnostic performance and is amenable to high throughput scaling up for a larger sample size at low cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1768-1789
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• 2015

The maximal signal-to-interference-plus-noise ratio (Max-SINR) algorithm for interference alignment (IA) has received considerable attention for its high sum rate achievement in the multiple-input multiple-output (MIMO) interference channel. However, its complexity may increase dramatically when the number of users approaches the IA feasibility bound, and the number of iterations and computational time may become unacceptable. In this paper, we study the properties of the Max-SINR algorithm thoroughly by presenting theoretical insight into the algorithm and by providing the potential of reducing the overall computational cost. Furthermore, a novel IA algorithm based on the principle direction search is proposed, which can converge more rapidly than the conventional Max-SINR method. In the proposed algorithm, it searches along the principle direction, which is found to approximately point to the convergence values, and can approach the convergence solutions rapidly. In addition, the closed-form solution of the optimal step size can be formulated in the sense of minimal interference leakage. Simulation results demonstrate that the proposed algorithm outperforms the conventional minimal interference leakage and Max-SINR algorithms in terms of the convergence rate while guaranteeing the high throughput of IA networks.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.601-612
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• 2006

This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1179-1187
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• 2016

Through the rapid development of latest hardware technology, high performance as well as miniaturized size is the essentials of embedded system to meet various requirements from the society. It raises possibilities of genuine realization of IoT environment whose size and battery must be considered. However, the limitation of battery persistency and capacity restricts the long battery life time for guaranteeing real-time system. To maximize battery life time, low power technology which lowers the power consumption should be highly required. Previous researches mostly highlighted improving one single type of memory to increase ones efficiency. In this paper, reversely, considering multiple memories to optimize whole memory system is the following step for the efficient low power embedded system. Regarding to that fact, this paper suggests the study of volatile memory, whose capacity is relatively smaller but much low-powered, and non-volatile memory, which do not consume any standby power to keep data, to maximize the efficiency of the system. By executing function in specific memories, non-volatile and volatile memory, the quantitative analysis of power consumption is progressed. In spite of the opportunity cost of all of theses extra works to locate function in volatile memory, higher efficiencies of both power and energy are clearly identified compared to operating single non-volatile memory.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.3
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• pp.458-464
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• 2015

This paper proposes a portable 3-D scanning technique using a laser pointer. 3-D scanning is a process that acquires surface information from an 3-D object. There have been many studies on 3-D scanning. The methods of 3-D scanning are summarized into some methods based on multiple cameras, line lasers, and light pattern recognition. However, those methods has major disadvantages of their high cost and big size for portable appliances such as smartphones and digital cameras. In this paper, a 3-D scanning system using a low-cost and small-sized laser pointer are introduced to solve the problems. To do so, we propose a 3-D localization technique for a laser point. The proposed method consists of two main parts; one is a fast recognition of input images to obtain 2-D information of a point laser and the other is calibration based on the least-squares technique to calculate the 3-D information overall. To verified our method, we carry out experiments. It is proved that the proposed method provides 3-D surface information although the system is constructed by extremely low-cost parts such a chip laser pointer, compared to existing methods. Also, the method can be implemented in small-size; thus, it is enough to use in mobile devices such as smartphones.

• Progress in Medical Physics
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• v.22 no.1
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• pp.42-51
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• 2011

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.

• Journal of International Society for Simulation Surgery
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• v.1 no.1
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• pp.37-40
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• 2014

Purpose For living donor liver transplantation, liver segmentation is difficult due to the variability of its shape across patients and similarity of the density of neighbor organs such as heart, stomach, kidney, and spleen. In this paper, we propose an automatic segmentation of the liver using multi-planar anatomy and deformable surface model in portal phase of abdominal contrast-enhanced CT images. Method Our method is composed of four main steps. First, the optimal liver volume is extracted by positional information of pelvis and rib and by separating lungs and heart from CT images. Second, anisotropic diffusing filtering and adaptive thresholding are used to segment the initial liver volume. Third, morphological opening and connected component labeling are applied to multiple planes for removing neighbor organs. Finally, deformable surface model and probability summation map are performed to refine a posterior liver surface and missing left robe in previous step. Results All experimental datasets were acquired on ten living donors using a SIEMENS CT system. Each image had a matrix size of $512{\times}512$ pixels with in-plane resolutions ranging from 0.54 to 0.70 mm. The slice spacing was 2.0 mm and the number of images per scan ranged from 136 to 229. For accuracy evaluation, the average symmetric surface distance (ASD) and the volume overlap error (VE) between automatic segmentation and manual segmentation by two radiologists are calculated. The ASD was $0.26{\pm}0.12mm$ for manual1 versus automatic and $0.24{\pm}0.09mm$ for manual2 versus automatic while that of inter-radiologists was $0.23{\pm}0.05mm$. The VE was $0.86{\pm}0.45%$ for manual1 versus automatic and $0.73{\pm}0.33%$ for manaual2 versus automatic while that of inter-radiologist was $0.76{\pm}0.21%$. Conclusion Our method can be used for the liver volumetry for the pre-surgery planning of living donor liver transplantation.