• Journal of The Korean Astronomical Society
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• v.49 no.3
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• pp.93-107
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• 2016

Augmenting the Wide Field Infrared Survey Telescope (WFIRST) microlensing campaigns with intensive observations from a ground-based network of wide-field survey telescopes would have several major advantages. First, it would enable full two-dimensional (2-D) vector microlens parallax measurements for a substantial fraction of low-mass lenses as well as planetary and binary events that show caustic crossing features. For a significant fraction of the free-floating planet (FFP) events and all caustic-crossing planetary/binary events, these 2-D parallax measurements directly lead to complete solutions (mass, distance, transverse velocity) of the lens object (or lens system). For even more events, the complementary ground-based observations will yield 1-D parallax measurements. Together with the 1-D parallaxes from WFIRST alone, they can probe the entire mass range M ≳ M_⊕. For luminous lenses, such 1-D parallax measurements can be promoted to complete solutions (mass, distance, transverse velocity) by high-resolution imaging. This would provide crucial information not only about the hosts of planets and other lenses, but also enable a much more precise Galactic model. Other benefits of such a survey include improved understanding of binaries (particularly with low mass primaries), and sensitivity to distant ice-giant and gas-giant companions of WFIRST lenses that cannot be detected by WFIRST itself due to its restricted observing windows. Existing ground-based microlensing surveys can be employed if WFIRST is pointed at lower-extinction fields than is currently envisaged. This would come at some cost to the event rate. Therefore the benefits of improved characterization of lenses must be weighed against these costs.

• The KIPS Transactions:PartC
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• v.14C no.7
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• pp.553-558
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• 2007

In this paper, we introduce a set of structures and algorithms for communication efficient public key revocation in wireless sensor networks. Unlike the traditional networks, wireless sensor network is subjected to resources constraints. Thus, traditional public key revocation mechanisms such like the ordinary certificate revocation list is unsuitable to be used. This unsuitability is due to the huge size of required representation space for the different keys' identifiers and the revocation communication as the set of revoked keys grow. In this work, we introduce two communication-efficient schemes for the certificate revocation. In the first scheme, we utilize the complete subtree mechanism for the identifiers representation which is widely used in the broadcast encryption/user revocation. In the second scheme, we introduce a novel bit vector representation BVS which uses vector of relative identifiers occurrence representation. We introduce different revocation policies and present corresponding modifications of our scheme. Finally, we show how the encoding could reduce the communication overhead as well. Simulation results and comparisons are provided to show the value of our work.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.181-188
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• 2007

Undirected Rural Postman Problem(URPP) is a problem that finds a shortest tour traversing the given arcs at least once in a given network. The URPP is one of the basic network problems used in solving the various real-world problems. And it is known as NP-Complete. URPP is an arc-oriented problem that the direction of a tour in an arc has to be considered. Hence, In URPP, it is difficult to use the algorithm for Traveling Salesman Problem (TSP), which is a node-oriented problem, directly. This paper proposes the decoding algorithm using graph transformation in the genetic algorithm for URPP. That is, you can find the entire tour traversing without considering the direction of arcs by transforming the arc-oriented graph into the node-oriented graph. This paper compares the performances of the proposed algorithm with an existing algorithm. In the simulation results, the proposed algorithm obtained better than the existing algorithm

• Korean Circulation Journal
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• v.52 no.4
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• pp.280-287
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• 2022

Several studies have shown the benefit of complete revascularization (CR) over culprit-only percutaneous coronary intervention (PCI) in patients with ST-segment elevated myocardial infarction (STEMI) and multivessel disease (MVD). Nevertheless, optimal strategy to select targets for non-culprit PCI has not been clarified. In this paper, we critically discuss and compare the safety and efficacy of different strategies for CR in patients with STEMI and MVD using a Bayesian network meta-analysis including all previous randomized controlled trials (RCTs). In Bayesian network meta-analysis of 13 RCTs, culprit-only PCI was associated with higher risk of major adverse cardiac events (MACE), compared with angiography-guided or fractional flow reserve (FFR)-guided CR strategies. However, there was no significant difference between angiography-guided and FFR-guided CR strategies in the risk of MACE and its individual components including all-cause death, cardiac death, myocardial infarction (MI), and revascularization. These evidence support that both angiography-guided and FFR-guided complete revascularization strategies would be reasonable treatment option in patients with STEMI and MVD. If the non-culprit lesion is severe on visual assessment, angiography-guided PCI can be considered. If the non-culprit lesion is intermediate in severity or unclear based on visual assessment, FFR-guided strategy can be used as a reliable and objective tool, providing similar benefits with less stents compared with an angiography-guided strategy. Further RCT is needed to evaluate direct comparison between angiography-guided and FFR-guided CR strategies in patients with STEMI and MVD. Ongoing FRAME-AMI trial (NCT02715518) will provide more evidence regarding this issue.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2185-2196
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• 1997

The existing information retrieval systems utilize thesaurus in order to search and retrieve the desired information even when the query is not accurate. However the cost for implementing and maintaining thesaurus is very high and it can not guarantee complete success of search/retrieval operation. Thus in this paper, Information Retrieval System using Keyword Network(KNetIRS) which was designed and implemented to solve these problem is introduced. Keyword Network composed of keywords which were extracted from documents. KNetIRS finds the appropriate documents by using the Keyword Network which is based on the concept of "inverted file". In addition, KNetIRS can carry out query expansion by using the Keyword Network Browser, and deal with the conjunction of "정보 검색", "정보", and "검색", by defining and implementing spilt function.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.819-824
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• 2015

SDN (Software Defined Network) technology, hardware and network control functions should be separated independently of existing switches or routers and data transfer functions and are also refers to a separate network architecture that can develop and run. When planning a network and designed to reflect the network control function by applying the SDN may reflect the resources efficiently. In this study, one people suggest Applications SDN, which offer an absolutely necessary part of a coded program that combines the benefits of the existing IOS (Combined Benefits) applying the model to complete the Controller part through the MPLS IOS. The OpenFlow Controller is a command to the router LER(Label Edge Router), and transmits the packet in accordance with the command to the destination according to the EXP bit. To configure TCP / IP to the IOS through the optimized coding. Using the OpenFlow protocol controller transmits an encapsulation header as defined in the MPLS packet.

• Radiation Oncology Journal
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• v.36 no.4
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• pp.276-284
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• 2018

Purpose: Traditionally, three-dimensional conformal radiation therapy (3D-CRT) is used for neoadjuvant chemoradiation in locally advanced rectal cancer. Intensity-modulated radiation therapy (IMRT) was later developed for more conformal dose distribution, with the potential for reduced toxicity across many disease sites. We sought to use the National Cancer Database (NCDB) to examine trends and predictors for IMRT use in rectal cancer. Materials and Methods: We queried the NCDB from 2004 to 2015 for patients with rectal adenocarcinoma treated with neoadjuvant concurrent chemoradiation to standard doses followed by surgical resection. Odds ratios were used to determine predictors of IMRT use. Univariable and multivariable Cox regressions were used to determine potential predictors of overall survival (OS). Propensity matching was used to account for any indication bias. Results: Among 21,490 eligible patients, 3,131 were treated with IMRT. IMRT use increased from 1% in 2004 to 22% in 2014. Predictors for IMRT use included increased N stage, higher comorbidity score, more recent year, treatment at an academic facility, increased income, and higher educational level. On propensity-adjusted, multivariable analysis, male gender, increased distance to facility, higher comorbidity score, IMRT technique, government insurance, African-American race, and non-metro location were predictive of worse OS. Of note, the complete response rate at time of surgery was 28% with non-IMRT and 21% with IMRT. Conclusion: IMRT use has steadily increased in the treatment of rectal cancer, but still remains only a fraction of overall treatment technique, more often reserved for higher disease burden.

• Journal of Korea Water Resources Association
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• v.54 no.1
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• pp.49-60
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• 2021

This study presents a methodology to estimate two distinct fractal dimensions of natural river basin by using fractal tree concept. To this end, an analysis is performed on fractal features of a complete drainage network which consists of all possible drainage paths within a river basin based on the growth process of fractal tree. The growth process of fractal tree would occur only within the limited drainage paths possessing stream flow features in a river basin. In the case of small river basin, the bifurcation process of network is more sensitive to the growth step of fractal tree than the meandering process of stream segment, so that various bifurcation structures could be generated in a single network. Therefore, fractal dimension of network structure for small river basin should be estimated in the form of a range not a single figure. Furthermore, the network structures with fractal tree from this study might be more useful information than stream networks from a topographic or digital map for analysis of drainage structure on small river basin.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.31-40
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• 2023

Objectives: This study investigated the effect of cognitive impairment on the association between social network properties and mortality among older Korean adults. Methods: This study used data from the Korean Social Life, Health, and Aging Project. It obtained 814 older adults' complete network maps across an entire village in 2011-2012. Participants' deaths until December 31, 2020 were confirmed by cause-of-death statistics. A Cox proportional hazards model was used to assess the risks of poor social network properties (low degree centrality, perceived loneliness, social non-participation, group-level segregation, and lack of support) on mortality according to cognitive impairment. Results: In total, 675 participants (5510.4 person-years) were analyzed, excluding those with missing data and those whose deaths could not be verified. Along with cognitive impairment, all social network properties except loneliness were independently associated with mortality. When stratified by cognitive function, some variables indicating poor social relations had higher risks among older adults with cognitive impairment, with adjusted hazard ratios (HRs) of 2.12 (95% confidence interval [CI], 1.34 to 3.35) for social nonparticipation, 1.58 (95% CI, 0.94 to 2.65) for group-level segregation, and 3.44 (95% CI, 1.55 to 7.60) for lack of support. On the contrary, these effects were not observed among those with normal cognition, with adjusted HRs of 0.73 (95% CI, 0.31 to 1.71), 0.96 (95% CI, 0.42 to 2.21), and 0.95 (95% CI, 0.23 to 3.96), respectively. Conclusions: The effect of social network properties was more critical among the elderly with cognitive impairment. Older adults with poor cognitive function are particularly encouraged to participate in social activities to reduce the risk of mortality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.