• Analytical Science and Technology
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• v.36 no.6
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• pp.259-266
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• 2023

The demand for rare-earth elements (REEs) is increasing owing to their significance as prominent materials in electronics, high-tech industries, geological research, nuclear forensics, and environmental monitoring. In general, the utilization of REEs in various applications requires the use of chromatographic techniques to separate individual elements. However, REEs have similar physicochemical properties, which makes them difficult to separate. Recently, several studies have examined the separation of REEs using LN resin as the stationary phase and aqueous nitric acid and hydrochloric acid solutions as eluents. Using this method, light REEs have been separated using dilute acid solutions as the eluent, whereas heavy REEs are separated using solutions with high acid concentrations. To increase the separation resolution between different REEs, either the column length or resin size is changed. In addition, the suggested methods are implemented to decrease the analysis time. This review presents technical information on the chromatographic separation of REEs using the LN resin and discusses the optimal experimental conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.23-30
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• 2022

Recently, there are various studies underway on the deep learning-used image matting methods. Even in the field of photogrammetry, a process of extracting information about relics from images photographed is essential to produce a high-quality realistic model. Such a process requires a great deal of time and manpower, so chroma-key has been used for extraction so far. This method is low in accuracy of sub-classification, however, it is difficult to apply the existing method to high-quality realistic models. Thus, this study attempted to remove background information from high-resolution relic images by using prior background information and trained learning data and evaluate both qualitative and quantitative results of the relic images extracted. As a result, this proposed method with FBA(manual trimap) showed quantitatively better results, and even in the qualitative evaluation, it was high in accuracy of classification around relics. Accordingly, this study confirmed the applicability of the proposed method in the indoor relic photography since it showed high accuracy and fast processing speed by acquiring prior background information when classifying high-resolution relic images.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.115-126
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• 2002

A mesoscale meteorological model is applied to simulate turbulent airflow and eddy shedding over the Isle of Arran, SW Scotland, UK. Under conditions of NW flow, the mountain ridge of Kintyre, located upwind of Arran, induces gravity waves that also affect the airflow over the island. The possibility to nest domains allows description of the airflow over Arran with a very high resolution grid, while also including the effects of the surrounding mainland of Scotland, in particular of the mountain ridge of Kintyre. Initialised with a stably stratified NW flow, the mesoscale model simulates quasi-stationary gravity waves over the island induced by Kintyre. Embedded in the larger scale wave trains there is continuous development of small-scale transient eddies, created at the Arran hill tops, that move downstream through the stationary wave field. Although the transient eddies are more frequently simulated on the northern island where the terrain is more pronounced, they are also produced over Tighvein, a hill of 458 m on the southern island where measurements of surface pressure and 2 m meteorological variables have been recorded at intermittent intervals between 1996 and 2000. Comparison between early observations and simulations so far show qualitatively good agreement. Overall the computations demonstrate that turbulent flow can be modelled with a horizontal resolution of 70 m, and describe turbulent eddy structure on wavelength of only a few hundred metres.

• Journal of The Korean Astronomical Society
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• v.40 no.4
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• pp.131-132
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• 2007

The research of OH maser emission sources with high angular resolution is complicated by the effects of interstellar scattering: more over, most of the OH maser sources are located in the galactic plane where the scattering is largest. However, the data available from pulsar studies on the spatial distribution of the amount of scattering indicate that there is a strong non-uniformity in the distribution of the amount of scattering material. There are directions in the galactic plane where the scattering is an order of magnitude higher than the average, as well as directions where the scattering is much lower. The latter provide an opportunity to investigate OH masers with the full angular resolution offered by very long baseline interferometry instruments, like the VLBA, and measure their true angular size, shape and brightness temperature. We have observed approximately 100 OH maser sources, distributed all over the northern hemisphere, with the VLBA in order to study the scattering properties of the interstellar medium.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.82-94
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• 2004

This paper addresses solutions to the challenges of carrier phase integer ambiguity resolution and cycle slip detection/identification, for maintaining high accuracy of an integrated GPS/Pseudolite/INS system. Such a hybrid positioning and navigation system is an augmentation of standard GPS/INS systems in localized areas. To achieve the goal of high accuracy, the carrier phase measurements with correctly estimated integer ambiguities must be utilized to update the system integration filter's states. The occurrence of a cycle slip that is undetected is, however, can significantly degrade the filter's performance. This contribution presents an effective approach to increase the reliability and speed of integer ambiguity resolution through using pseudolite and INS measurements, with special emphasis on reducing the ambiguity search space. In addition, an algorithm which can effectively detect and correct the cycle slips is described as well. The algorithm utilizes additional position information provided by the INS, and applies a statistical technique known as the cumulative-sum (CUSUM) test that is very sensitive to abrupt changes of mean values. Results of simulation studies and field tests indicate that the algorithms are performed pretty well, so that the accuracy and performance of the integrated system can be maintained, even if cycle slips exist in the raw GPS measurements.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.1 s.24
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• pp.29-37
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• 2003

The High-resolution satellite images are able to get the latest information of wide range area and to shorten updating cycle of digital map better than the aerial images. Especially, as high-resolution satellite images are opened to public recently and able to be used commercially, the studies that make ortho-images using them and apply to the digital mapping and the database of geo-spatial information system are having been progressed actively. Therefore, the purposes of this study are to establish the auto-extraction methods and to develop algorithms for automatically extracting buildings which are distributed very much in urban areas and which updating cycle needs to shorten, out of man-made structures in the IKONOS ortho-image with 1m spatial resolution. The result of this study, we can extract automatically extract 72% out of the whole buildings. And we could know that the methods and algorithms proposed in this study are good relatively analyzing the error trend by means of the comparison with ortho-image, digital map and hawing result.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• Bulletin of the Korean Chemical Society
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• v.34 no.3
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• pp.823-826
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• 2013

A low-${\varepsilon}$ solid-state NMR(Nuclear Magnetic Resonance) probe was developed for the spectroscopic analysis of two-dimensional $^{15}N-^1H$ heteronuclear dipolar coupling in dilute membrane proteins oriented in hydrated and dielectrically lossy lipid environments. The system employed a 800 MHz narrow-bore magnet. A solenoid coil strip shield was used to reduce deleterious RF sample heating by minimizing the conservative electric fields generated by the double-tuned resonator at high magnetic fields. The probe's design, construction, and performance in solid-state NMR experiments at high magnetic fields are described here. Such high-resolution solid-state NMR spectroscopic analysis of static oriented samples in hydrated phospholipid bilayers or bicelles could aid the structural analysis of dilute biological membrane proteins.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.46-56
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• 2004

As economic cooperation and exchanges between North and South Korea have been glowing much more than before, the demand for geographic information on North Korea is recently increasing. In fact, there is no specific method to be provided with geographic information on North Korea. In this regard, the study searched a method to collect geographic information on North Korea by using the high spatial resolution satellite image. In order to produce its best result, the study collected the geographic information on the case study area and ensured the location accuracy. This study produced total 52 items of geographic information on North Korea. Horizontal and vertical errors of stereo image, which are 4.6m and 0.9m respectively, showed high accuracy. In addition, even though the horizontal error of single image is 9m, which is bigger than that of stereo image, there is no doubt that it can be used as basic data for North Korean studies and related projects.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.113-114
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• 2013

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging is a powerful technique for producing chemical images of small biomolecules (ex. metabolites, lipids, peptides) "as received" because of its high molecular specificity, high surface sensitivity, and submicron spatial resolution. In addition, matrix-assisted laser desorption and ionization time-of-flight (MALDI-TOF) imaging is an essential technique for producing chemical images of large biomolecules (ex. genes and proteins). For this talk, we will show that label-free mass imaging technique can be a platform technology for biomedical studies such as early detection/diagnostics, accurate histologic diagnosis, prediction of clinical outcome, stem cell therapy, biosensors, nanomedicine and drug screening [1-7].