• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.4
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• pp.55-60
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• 2018

The thermal property is one of the most important characteristics in the field of energetic materials. Because energy materials release decomposition heat, differential scanning calorimetry (DSC) is frequently used for thermal analysis. However, thermodynamic events, such as melting can interfere with DSC kinetic analysis. In this study, we use isothermal mode for DSC measurement to avoid thermodynamic issues. We also merge accelerating rate calorimetry(ARC) data with DSC data to obtain a robust prediction results for small scale samples and for large scale samples as well. For the thermal property prediction, advanced kinetics and technology solutions(AKTS) programs are used.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.91-92
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• 2019

본 논문에서는 IoT 기기의 각 센서로부터 획득된 데이터에 대한 수집 및 효율적 라우팅 기법을 기반으로 대용량 데이터 수집의 효율성 및 신뢰도 향상을 위해 In-network 데이터 병합 기반 데이터 전처리 기법을 제안한다. 기존의 Wireless Sensor Network에서는 모든 단말 노드가 스스로 라우팅 된 하위 센서 노드들의 데이터를 병합하는 In-network 병합기법을 사용한다. 이 기법은 이벤트가 발생하지 않거나 필요한 쿼리가 없어도 주기적으로 라우팅에 필요한 메시지를 전송하므로 불필요한 에너지 소모를 야기 시키며 데이터 전송 에러가 발생할 확률이 높다. 기존 In-Network 데이터 병합 기법의 효율성 및 정확성을 향상시키기 위해, 본 논문에서는 조건 병합 기반의 In-network 병합 기법을 제안한다.

• Genomics & Informatics
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• v.19 no.3
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• pp.23.1-23.7
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• 2021

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.165-187
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• 2018

Despite repeated efforts to develop a methodological foundation for assembling collaborative authority data in South Korea, issues such as the establishment of a standard authority model and standard authority construction as well as the reconfiguration of existing entities in authority building have prevented such research from generating a cooperative push for nation-wide authority data and progressing toward concrete implementation. The formulation of a collaborative and well-utilized collection of national authority data accordingly calls for 1) a practical approach to supporting both established authority data contributors and newly organized avenues of mutual participation in authority building, 2) committed involvement on the part of national institutions capable of providing the project with sustained assistance, and 3) a standard identification system which allows multiple organizations to merge their data. This study addresses the challenges of the current environment by taking stock of the key components necessary for the creation of collaborative authority data and using a Semantic Web-based interoperable VIVO ontology model to propose a viable national authority data framework.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.215-223
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• 2008

Due partly to lack of actual lane-changing data and partly to few studies on simulation functions to consider the lane-changing behavior, it may result in significant difference between simulation-based and real conditions. The objectives of this study are to estimate the set of mandatory lane-changing models and to analyze their features, depending on the merge control strategies under the lane-closed work zone operations. To achieve them, first, the elaborated calibration is required to simulate the mandatory lane-changing behaviors with the actual field data. Second, one can estimate their models with the logistic regression models, to obtain traffic variables as well as the lane-changing frequencies under the various levels of work zone traffic conditions. As a result, one can state that the well-calibrated simulation has the potential to properly reflect the target mandatory lane-changing behaviors. In addition, it should be mentioned that the set of proposed models is not practicable but preliminary result needed to identify the relations between the actual traffic conditions and lane-changing maneuvers and to develop their practical models for the actual applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1562-1578
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• 2020

Vector data compression algorithm can meet requirements of different levels and scales by reducing the data amount of vector graphics, so as to reduce the transmission, processing time and storage overhead of data. In view of the fact that large threshold leading to comparatively large error in Douglas-Peucker vector data compression algorithm, which has difficulty in maintaining the uncertainty of shape features and threshold selection, a segmented Douglas-Peucker algorithm based on node importance is proposed. Firstly, the algorithm uses the vertical chord ratio as the main feature to detect and extract the critical points with large contribution to the shape of the curve, so as to ensure its basic shape. Then, combined with the radial distance constraint, it selects the maximum point as the critical point, and introduces the threshold related to the scale to merge and adjust the critical points, so as to realize local feature extraction between two critical points to meet the requirements in accuracy. Finally, through a large number of different vector data sets, the improved algorithm is analyzed and evaluated from qualitative and quantitative aspects. Experimental results indicate that the improved vector data compression algorithm is better than Douglas-Peucker algorithm in shape retention, compression error, results simplification and time efficiency.

• Korean Journal of Remote Sensing
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• v.14 no.2
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• pp.149-164
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• 1998

The main object of this study was to prove the effectiveness of different merging methods by using the high resolution IRS(Indian Remote Sensing Satellite)-1C panchromatic data and the multispectral Landsat TM data. The five methods used to merging the information contents of each of the satellite data were the intensity-hue-saturation(IHS), principal component analysis(PCA), high pass filter(HPF), ratio enhancement method and look-up-table(LUT) procedures. Two measures are used to evaluate the merging method. These measures include visual inspection and comparisons of the mean, standard deviation and root mean square error between merged image and original image data values of each band. The ratio enhancement method was well preserved the spectral characteristics of the data. From visual inspection, PCA method provide the best result, HPF next, ratio enhancement, IHS and LUT method the worst for the preservation of spatial resolution.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.262-266
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• 1999

Several commercial companies that plan to provide improved panchromatic and/or multi-spectral remote sensor data in the near future are suggesting that merge datasets will be of significant value. This study evaluated the utility of one major merging process-process components analysis and its inverse. The 6 bands of 30$\times$30m Landsat TM data and the 10$\times$l0m SPOT panchromatic data were used to create a new 10$\times$10m merged data file. For the image classification, 6 bands that is 1st, 2nd, 3rd, 4th, 5th and 7th band may be used in conjunction with supervised classification algorithms except band 6. One of the 7 bands is Band 6 that records thermal IR energy and is rarely used because of its coarse spatial resolution (120m) except being employed in thermal mapping. Because SPOT panchromatic has high resolution it makes 10$\times$10m SPOT panchromatic data be used to classify for the detailed classification. SPOT as the Landsat has acquired hundreds of thousands of images in digital format that are commercially available and are used by scientists in different fields. After the merged, the classifications used supervised classification and neural network. The method of the supervised classification is what used parallelepiped and/or minimum distance and MLC(Maximum Likelihood Classification) The back-propagation in the multi-layer perception is one of the neural network. The used method in this paper is MLC(Maximum Likelihood Classification) of the supervised classification and the back-propagation of the neural network. Later in this research SPOT systems and images are compared with these classification. A comparative analysis of the classifications from the TM and merged SPOT/TM datasets will be resulted in some conclusions.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.640-652
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• 2012

Many studies have investigated the smart grid architecture and communication models in the past few years. However, the communication model and architecture for a smart grid still remain unclear. Today's electric power distribution is very complex and maladapted because of the lack of efficient and cost-effective energy generation, distribution, and consumption management systems. A wireless smart grid communication system can play an important role in achieving these goals. In this paper, we describe a smart grid communication architecture in which we merge customers and distributors into a single domain. In the proposed architecture, all the home area networks, neighborhood area networks, and local electrical equipment form a local wireless mesh network (LWMN). Each device or meter can act as a source, router, or relay. The data generated in any node (device/meter) reaches the data collector via other nodes. The data collector transmits this data via the access point of a wide area network (WAN). Finally, data is transferred to the service provider or to the control center of the smart grid. We propose a wireless cooperative communication model for the LWMN.We deploy a limited number of smart relays to improve the performance of the network. A novel relay selection mechanism is also proposed to reduce the relay selection overhead. Simulation results show that our cooperative smart grid (coopSG) communication model improves the end-to-end packet delivery latency, throughput, and energy efficiency over both the Wang et al. and Niyato et al. models.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.849-862
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• 2017

The increased frequency of meteorological disasters has been observed due to increased extreme events such as heavy rainfalls and flash floods. Numerous studies using high-resolution weather radar rainfall data have been carried out on the hydrological effects. In this study, a conditional merging technique is employed, which makes use of geostatistical methods to extract the optimal information from the observed data. In this context, three different techniques such as kriging, inverse distance weighting and spline interpolation methods are applied to conditionally merge radar and ground rainfall data. The results show that the estimated rainfall not only reproduce the spatial pattern of sub-hourly rainfall with a relatively small error, but also provide reliable temporal estimates of radar rainfall. The proposed modeling framework provides feasibility of using conditionally merged rainfall estimation at high spatio-temporal resolution in ungauged areas.