• Progress in Medical Physics
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• v.23 no.4
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• pp.309-316
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• 2012

Multimodal-imaging technique has been rapidly developed for improvement of diagnosis and evaluation of therapeutic effects. In despite of integrated hardware, registration accuracy was decreased due to a discrepancy between multimodal image and insufficiency of count in accordance with different acquisition method of each modality. The purpose of this study was to improve the PET image by event data resampling through analysis of data format, noise and statistical properties of small animal PET list data. Inveon PET listmode data was acquired as static data for 10 min after 60 min of 37 MBq/0.1 ml $^{18}F$-FDG injection via tail vein. Listmode data format was consist of packet containing 48 bit in which divided 8 bit header and 40 bit payload space. Realigned sinogram was generated from resampled event data of original listmode by using adjustment of LOR location, simple event magnification and nonparametric bootstrap. Sinogram was reconstructed for imaging using OSEM 2D algorithm with 16 subset and 4 iterations. Prompt coincidence was 13,940,707 count measured from PET data header and 13,936,687 count measured from analysis of list-event data. In simple event magnification of PET data, maximum was improved from 1.336 to 1.743, but noise was also increased. Resampling efficiency of PET data was assessed from de-noised and improved image by shift operation of payload value of sequential packet. Bootstrap resampling technique provides the PET image which noise and statistical properties was improved. List-event data resampling method would be aid to improve registration accuracy and early diagnosis efficiency.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.40-46
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• 2009

Purpose : The purpose of this study was to investigate the quantitative evaluation of the corticospinal tract (CST) at the multiple levels by using functional MRI (fMRI) co-registered to diffusion tensor tractography (DTT). Materials and Methods : Ten normal subjects without any history of neurological disorder participated in this study. fMRI was performed at 1.5 T MR scanner using hand grasp-release movement paradigm. DTT was performed by using DtiStudio on the basis of fiber assignment continuous tracking algorithm (FACT). The seed region of interest (ROI) was drawn in the area of maximum fMRI activation during the motor task of hand grasp-release movement on a 2-D fractional anisotropy (FA) color map, and the target ROI was drawn in the cortiocospinal portion of anterior lower pons. We have drawn five ROIs for the measurement of FA and apparent diffusion coefficient (ADC) along the corona radiata (CR) down to the medulla. Results : The contralateral primary sensorimotor cortex (SM1) was mainly found to be activated in all subjects. DTT showed that tracts originated from SM1 and ran to the medulla along the known pathway of the CST. In all subjects, FA values of the CST were higher at the level of the midbrain and posterior limb of internal capsule (PLIC) than the level of others. Conclusion : Our study showed that co-registered fMRI and DTT has elucidated the state of CST on 3-D and analyzed the quantitative values of FA and ADC at the multiple levels. We conclude that co-registered fMRI and DTT may be applied as a useful tool for clarifying and investigating the state of CST in the patients with brain injury.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.7
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• pp.380-394
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• 2015

This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2014. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of heat and mass transfer, cooling and heating, and air-conditioning, the flow inside building rooms, and smoke control on fire. Research issues dealing with duct and pipe were reduced, but flows inside building rooms, and smoke controls were newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for thermal contact resistance measurement of metal interface, a fan coil with an oval-type heat exchanger, fouling characteristics of plate heat exchangers, effect of rib pitch in a two wall divergent channel, semi-empirical analysis in vertical mesoscale tubes, an integrated drying machine, microscale surface wrinkles, brazed plate heat exchangers, numerical analysis in printed circuit heat exchanger. In the area of pool boiling and condensing, non-uniform air flow, PCM applied thermal storage wall system, a new wavy cylindrical shape capsule, and HFC32/HFC152a mixtures on enhanced tubes, were actively studied. In the area of industrial heat exchangers, researches on solar water storage tank, effective design on the inserting part of refrigerator door gasket, impact of different boundary conditions in generating g-function, various construction of SCW type ground heat exchanger and a heat pump for closed cooling water heat recovery were performed. (3) In the field of refrigeration, various studies were carried out in the categories of refrigeration cycle, alternative refrigeration and modelling and controls including energy recoveries from industrial boilers and vehicles, improvement of dehumidification systems, novel defrost systems, fault diagnosis and optimum controls for heat pump systems. It is particularly notable that a substantial number of studies were dedicated for the development of air-conditioning and power recovery systems for electric vehicles in this year. (4) In building mechanical system research fields, seventeen studies were reported for achieving effective design of the mechanical systems, and also for maximizing the energy efficiency of buildings. The topics of the studies included energy performance, HVAC system, ventilation, and renewable energies, piping in the buildings. Proposed designs, performance performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment was mostly focused on indoor environment and building energy. The main researches of indoor environment were related to the evaluation of work noise in tunnel construction and the simulation and development of a light-shelf system. The subjects of building energy were worked on the energy saving of office building applied with window blind and phase change material(PCM), a method of existing building energy simulation using energy audit data, the estimation of thermal consumption unit of apartment building and its case studies, dynamic window performance, a writing method of energy consumption report and energy estimation of apartment building using district heating system. The remained studies were related to the improvement of architectural engineering education system for plant engineering industry, estimating cooling and heating degree days for variable base temperature, a prediction method of underground temperature, the comfort control algorithm of car air conditioner, the smoke control performance evaluation of high-rise building, evaluation of thermal energy systems of bio safety laboratory and a development of measuring device of solar heat gain coefficient of fenestration system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.29-45
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• 2015

Systematic theory, concepts, and methodology for the biological evolution have been developed while patterns and principles of the evolution have been actively studied in the past 200 years. Furthermore, they are applied to various fields such as evolutionary economics, evolutionary psychology, evolutionary linguistics, making significant progress in research. In addition, existing studies have applied main biological evolutionary models to artifacts although such methods do not fit to them. These models are also limited to generalize evolutionary patterns of artifacts because they are designed in terms of a subjective point of view of experts who know well about the artifacts. Unlike biological organisms, because artifacts are likely to reflect the imagination of the human will, it is known that the theory of biological evolution cannot be directly applied to artifacts. In this paper, beyond the individual's subjective, the aim of our research is to present evolutionary patterns of a given artifact based on peeping the idea of the public. For this, we propose a text mining approach that presents a systematic framework that can find out the evolutionary patterns of a given artifact and then visualize effectively. In particular, based on our proposal, we focus mainly on a case study of mobile phone that has emerged as an icon of innovation in recent years. We collect and analyze review posts on mobile phone available in the domestic market over the past decade, and discuss the detailed results about evolutionary patterns of the mobile phone. Moreover, this kind of task is a tedious work over a long period of time because a small number of experts carry out an extensive literature survey and summarize a huge number of materials to finally draw a diagram of evolutionary patterns of the mobile phone. However, in this work, to minimize the human efforts, we present a semi-automatic mining algorithm, and through this research we can understand how human creativity and imagination are implemented. In addition, it is a big help to predict the future trend of mobile phone in business and industries.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.887-898
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• 2007

A physically based semi-distributed model, SWAT was applied to the Chungju Dam upstream watershed in order to investigate the spatial and temporal characteristics of watershed sediment yields. For this, general features of the SWAT and sediment simulation algorithm within the model were described briefly, and watershed sediment modeling system was constructed after calibration and validation of parameters related to the runoff and sediment. With this modeling system, temporal and spatial variation of soil loss and sediment yields according to watershed scales, land uses, and reaches was analyzed. Sediment yield rates with drainage areas resulted in $0.5{\sim}0.6ton/ha/yr$ excluding some upstream sub-watersheds and showed around 0.51 ton/ha/yr above the areas of $1,000km^2$. Annual average soil loss according to land use represented the higher values in upland areas, but relatively lower in paddy and forest areas which were similar to the previous results from other researchers. Among the upstream reaches, Pyeongchanggang and Jucheongang showed higher sediment yields which was thought to be caused by larger area and higher fraction of upland than other upstream sub-areas. Monthly sediment yields at the main outlet showed same trend with seasonal rainfall distribution, that is, approximately 62% of annual yield was generated during July to August and the amount was about 208 ton/yr. From the results, we could obtain the uniform value of sediment yield rate and could roughly evaluate the effect of soil loss with land uses, and also could analyze the temporal and spatial characteristics of sediment yields from each reach and monthly variation for the Chungju Dam upstream watershed.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.107-123
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• 2020

With stabilization of the recent multi-GNSS infrastructure, and as multi-GNSS has been proven to be effective in improving the accuracy of the positioning performance in various industrial sectors. In this study, in view that SF(Single frequency) GNSS receivers are widely used due to the low costs, evaluate effectiveness of SF Real Time Point Positioning(SF-RT-PP) based on four multi-GNSS surveying methods with RTCM-SSR correction streams in static and kinematic modes, and also derive response challenges. Results of applying SSR correction streams, CNES presented good results compared to other SSR streams in 2D coordinate. Looking at the results of the SF-RT-PP surveying using SF signals from multi-GNSS, were able to identify the common cause of large deviations in the altitude components, as well as confirm the importance of signal bias correction according to combinations of different types of satellite signals and ionospheric delay compensation algorithm using undifferenced and uncombined observations. In addition, confirmed that the improvement of the infrastructure of Multi-GNSS allows SF-RT-SPP surveying with only one of the four GNSS satellites. In particular, in the case of code-based SF-RT-SPP measurements using SF signals from GPS satellites only, the difference in the application effect between broadcast ephemeris and SSR correction for satellite orbits/clocks was small, but in the case of ionospheric delay compensation, the use of SBAS correction information provided more than twice the accuracy compared to result of the Klobuchar model. With GPS and GLONASS, both the BDS and GALILEO constellations will be fully deployed in the end of 2020, and the greater benefits from the multi-GNSS integration can be expected. Specially, If RT-ionospheric correction services reflecting regional characteristics and SSR correction information reflecting atmospheric characteristics are carried out in real-time, expected that the utilization of SF-RT-PPP survey technology by multi-GNSS and various demands will be created in various industrial sectors.

• Journal of the Korean earth science society
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• v.39 no.5
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• pp.419-435
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• 2018

The purpose of this study is to understand meteorological and climatological factors that have influence on the garlic product in Seosan and Taean, and to analyze the economic value according to the use of climatical information data for garlic farmers. The climatological characteristics and trends in this area are analyzed using the meteorological data at the Seosan local meteorological agency from 1984 to 2013, the national statistical data for the product of garlic from 1989 to 2013, and the scenario data for climate change (RCP 4.5 and 8.5) for the period from 2001 to 2100. The results are as follows. First, the condition of lower temperature for garlic growth in winter season is satisfied with the mean air temperature. The wind speed are lower and stronger in Seosan and Taean than other garlic area. The suitable condition for the growth of northern type of garlic shows the decreasing trend in the accumulated precipitation in May. However, the area of growing the northern type garlic in the future is likely diminished because mean air temperature, accumulated precipitation, and mean wind speed are strong in the harvest time of garlic. Second, the seedtime of the northern and southern type of garlic using climate change scenarios (RCP 4.5, 8.5) in Seosan and Taean is getting late as time passes. and the harvest time gets faster, which indicates s that the period of garlic cultivation becomes shorter from 50 days to around 90 in the next 100 years. Third, the beginning days of white rot and delia platura of garlic are estimated by applying to the meteorological algorithm using mean air temperature and soil humidity. Especially, the beginning day of white rot garlic is shown to be faster according to the scenarios of RCP 4.5 and RCP 8.5. Fourth, the product of garlic (kg/10a) shows a high correlation with the minimum air temperature of a wintering time, the mean wind speed of a wintering time, the accumulated precipitation of a corpulent time, and the mean relative humidity of corpulent time of garlic. On the other hand, the analysis of garlic product when using the meteorological information data in cultivating garlic in Seosan and Taean reveals that the economic value increases up to 9% in total.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.4
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• pp.479-488
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• 2002

In recent years the amount of digital video used has risen dramatically to keep pace with the increasing use of the Internet and consequently an automated method is needed for indexing digital video databases. Textual information, both superimposed and embedded scene texts, appearing in a digital video can be a crucial clue for helping the video indexing. In this paper, a new method is presented to extract both superimposed and embedded scene texts in a freeze-frame of news video. The algorithm is summarized in the following three steps. For the first step, a color image is converted into a gray-level image and applies contrast stretching to enhance the contrast of the input image. Then, a modified local adaptive thresholding is applied to the contrast-stretched image. The second step is divided into three processes: eliminating text-like components by applying erosion, dilation, and (OpenClose+CloseOpen)/2 morphological operations, maintaining text components using (OpenClose+CloseOpen)/2 operation with a new Geo-correction method, and subtracting two result images for eliminating false-positive components further. In the third filtering step, the characteristics of each component such as the ratio of the number of pixels in each candidate component to the number of its boundary pixels and the ratio of the minor to the major axis of each bounding box are used. Acceptable results have been obtained using the proposed method on 300 news images with a recognition rate of 93.6%. Also, my method indicates a good performance on all the various kinds of images by adjusting the size of the structuring element.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.135-145
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• 2020

Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.