• Transactions on Electrical and Electronic Materials
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• v.1 no.4
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• pp.1-6
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• 2000

The mechanical strength of silicon carbide dose nor permit the use of diffusion as a means to achieve selective doping as required by most electronic devices. While epitaxial layers may be doped during growth, ion implantation is needed to define such regions as drain and source wells, junction isolation regions, and so on. Ion activation without an annealing cap results in serious crystal damage as these activation processes must be carried out at temperatures on the order of 1600$^{\circ}C$. Ion implanted silicon carbide that is annealed in either a vacuum or argon environment usually results in a surface morphology that is highly irregular due to the out diffusion of Si atoms. We have developed and report a successful process of using silicon overpressure, provided by silane in a CAD reactor during the anneal, to prevent the destruction of the silicon carbide surface, This process has proved to be robust and has resulted in ion activation at a annealing temperature of 1600$^{\circ}C$ without degradation of the crystal surface as determined by AFM and RBS. In addition XPS was used to look at the surface and near surface chemical states for annealing temperatures of up to 1700$^{\circ}C$. The surface and near surface regions to approximately 6 nm in depth was observed to contain no free silicon or other impurities thus indicating that the process developed results in an atomically clean SiC surface and near surface region within the detection limits of the instrument(${\pm}$1 at %).

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.473-490
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• 2022

Purpose: The purpose of this study is to propose a new useful suggestion to monitor the stability of process by developing a stability ratio or index related to investigating how well the process is controlled or operated to the specified target. Methods: The proposed method to monitor the stability of process is building up a new measure index which is making up for the weakness of the existing index in terms of short or long term period of production. This new index is a combined one considering both stability and capability of process to the specification limits. We suppose that both process mean and process variation(or deviation) are changing on time period. Results: The results of this study are as follows: regarding the stability of process as well as capability of process, it was shown that two indices, called SI(stability index) and PI(performance index), can be expressed in two-dimensional X-Y graph simultaneously. This graph is categorized as 4 separated partitions, which are characterized by its numerical value intervals of SI and PI which are evaluated by test statistics. Conclusion: The new revised index is more robust than the existing one in investigating the stability of process in terms of short and long period of production, even in case both process mean and variation are changing.

• Journal of Radiation Protection and Research
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• v.47 no.4
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• pp.181-194
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• 2022

Internal dosimetry is a discipline which brings together a set of knowledge, tools and procedures for calculating the dose received after incorporation of radionuclides into the body. Several steps are necessary to calculate the committed effective dose (CED) for workers or members of the public. Each step uses the best available knowledge in the field of radionuclide biokinetics, energy deposition in organs and tissues, the efficiency of radiation to cause a stochastic effect, or in the contributions of individual organs and tissues to overall detriment from radiation. In all these fields, knowledge is abundant and supported by many works initiated several decades ago. That makes the CED a very robust quantity, representing exposure for reference persons in reference situation of exposure and to be used for optimization and assessment of compliance with dose limits. However, the CED suffers from certain limitations, accepted by the International Commission on Radiological Protection (ICRP) for reasons of simplification. Some of its limitations deserve to be overcome and the ICRP is continuously working on this. Beyond the efforts to make the CED an even more reliable and precise tool, there is an increasing demand for personalized dosimetry, particularly in the medical field. To respond to this demand, currently available tools in dosimetry can be adjusted. However, this would require coupling these efforts with a better assessment of the individual risk, which would then have to consider the physiology of the persons concerned but also their lifestyle and medical history. Dosimetry and risk assessment are closely linked and can only be developed in parallel. This paper presents the state of the art of internal dosimetry knowledge and the limitations to be overcome both to make the CED more precise and to develop other dosimetric quantities, which would make it possible to better approximate the individual dose.

• Journal of Microbiology and Biotechnology
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• v.33 no.8
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• pp.1091-1100
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• 2023

Human papillomavirus (HPV) types 16 and 18 are the major causes of cervical lesions and are associated with 71% of cervical cancer cases globally. However, public health infrastructures to support cervical cancer screening may be unavailable to women in low-resource areas. Therefore, sensitive, convenient, and cost-efficient diagnostic methods are required for the detection of HPV16/18. Here, we designed two novel methods, real-time ERA and ERA-LFD, based on enzymatic recombinase amplification (ERA) for quick point-of-care identification of the HPV E6/E7 genes. The entire detection process could be completed within 25 min at a constant low temperature (35-43℃), and the results of the combined methods could be present as the amplification curves or the bands presented on dipsticks and directly interpreted with the naked eye. The ERA assays evaluated using standard plasmids carrying the E6/E7 genes and clinical samples exhibited excellent specificity, as no cross-reaction with other common HPV types was observed. The detection limits of our ERA assays were 10⁰ and 10¹ copies/µl for HPV16 and 18 respectively, which were comparable to those of the real-time PCR assay. Assessment of the clinical performance of the ERA assays using 114 cervical tissue samples demonstrated that they are highly consistent with real-time PCR, the gold standard for HPV detection. This study demonstrated that ERA-based assays possess excellent sensitivity, specificity, and repeatability for HPV16 and HPV18 detection with great potential to become robust diagnostic tools in local hospitals and field studies.

• Journal of Environmental Health Sciences
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• v.40 no.2
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• pp.114-126
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• 2014

Objectives: We aimed to develop a measurement method of five metabolites of trichloroethylene (TCE) in a concurrent biological sample, e.g., trichloroacetic acid (TCA), dichloroacetic acid (DCA), S-(1,2-dichlorovinyl) glutathione (DCVG), S-(1,2-dichlorovinyl)-L-cysteine (DCVC), and N-Acetyl-S-(1,2-dichlorovinyl)-L-cysteine (NAcDCVC) and to validate the method before application to pharmacokinetic study. Methods: TCE metabolites were simultaneously analyzed using high performance liquid chromatography coupled with electrospray ionization mass spectrometry (HPLC-ESI-MS/MS) with as little as 50 ${\mu}L$ of serum and urine. DCA, TCA and NAcDCVC were extracted with diethyl ether, while DCVC and DCVG were extracted by solid phase extraction. This method was validated according to the guidelines for bioanalytical method validation of the Korean National Institute of Toxicological Research. Then, we determined the five metabolites in five strains of mice at 24 hr after exposure to 1 g TCE /kg body weight. Results: The limits of detection for the five metabolites in biological samples ranged from 0.001 to 0.076 nmol/mL, which is comparable to or better than those previously reported. Most calibration curves showed good linearity ($R^2=0.99$), and between-batch variation was less than 20% expressing acceptable robustness and reproducibility. Using this method, we found TCA and DCA were detected in all test mice at 24 hr after the oral administration while NAcDCVC and DCVC were detected in some strains, which showed strain-dependent metabolism of TCE. Conclusions: The present method could provide robust and accurate measurements of major key metabolites of TCE in biological media, which allowed concurrent analysis of TCE metabolism for limited amounts of biospecimens.

• Journal of Life Science
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• v.28 no.1
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• pp.78-82
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• 2018

Detection of pathogenic microorganisms takes several days by conventional methods. It is necessary to assess microorganisms in a timely manner to reduce the risk of spreading infection. For this purpose, bacteriophages are chosen for use as a biosensing tool due to their host specificity, wide abundance, and safety. However, their lytic cycle limits their efficacy as biosensors. Phage proteins involved in binding to bacteria could be a robust alternative in resolving this drawback. Here, a fragment of tail protein J (residues 784 to 1,132) of phage lambda fused with 6X His-tag (6HN-J) at its N-terminus was cloned, overexpressed, purified, and characterized for its binding with microorganisms. The purified protein demonstrated a size of about 38 kDa in sodium dodecyl sulfate - polyacrylamide gel electrophoresis (SDS-PAGE) and bound with anti-His monoclonal antibodies. It bound specifically to Escherichia coli K-12, and not Salmonella typhimurium, Bacillus subtilis, or Pseudomonas aeruginosa in dot blotting. Binding of the protein to E. coli K-12 inhibited about 50% of the in vivo adsorption of the phage lambda to host cells at a concentration of $1{\mu}g/ml$ 6HN-J protein and almost 100% at $25{\mu}g/ml$ 6HN-J. The results suggest that a fusion viral protein could be utilized as a biosensing element (e.g., protein chips) for detecting microorganisms in real time.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.183-183
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• 2017

In the early part of rice growth, root volume primarily limits the amount of plant-accessible nitrogen (N). Therefore, knowledge of the root development is important for modeling N uptake of rice. The timing when the volume of rhizosphere cover the whole soil is also important to carry out timely top dressing. However, information about initial root expansion and associated N uptake is limited due to intrinsic technical difficulties in assessing below-ground processes. Some studies, however, showed a close relationship between below-ground root and above-ground leaf development, suggesting a possibility that above-ground attributes could serve as surrogates for the root processes. In this study, we investigated the relationship between below-ground and above-ground development of rice. Field experiments were conducted where we cultivated Koshihikari (a leading cultivar in Japan) for four different cropping schedules in 2012. In 2016, Gimbozu (HEG4) and three flowering time mutant lines of Gimbozu (X61 (se13), HS276 (ef7), DMG9 (se13, ef7)) were examined for a single season. Experiments were performed with three replications in a completely randomized design. We monitored ammonium-N concentration ([NH4+-N]) in soil solution by repeatedly taking samples from a porous tubing (10-cm long) vertically inserted at the most distant point from surrounding rice hills. Samples were taken in triplicate (= triplicate tubes) and every three days from transplanting in each experimental unit. For above-ground attributes, leaf area index (LAI) was measured in 2012, whereas soil coverage ratio was estimated by image processing in 2016. Results showed that [NH4+-N] increased gradually after transplanting and then rapidly decreased from a certain day. This distinct drop in [NH4+-N] informed us the timing at which the rice root system reached the point of porous tubing and thus essentially covered the whole soil volume. The LAI at the dropping point was about 0.43 regardless of the cropping schedules in 2012 experiment. In 2016, the coverage ratio at the N dropping point was within the range of 0.12 to 0.19 for four genotypes having different growth durations. In addition, the coverage ratios at seven weeks after the transplanting showed a good correspondence to LAI across the four genotypes. We therefore conclude that both LAI and coverage ratio may serve as robust indicators for root development and might be useful to estimate the timing when the root system fully cover the soil volume. Results obtained here will also contribute to develop models that can predict not only above-ground canopy development but also associated below-ground processes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.