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THE NEW ECLIPSING POST COMMON-ENVELOPE BINARY SDSS J074548.63+263123.4

  • HEMHA, NIWAT;SANGUANSAK, NUANWAN;IRAWATI, PUJI;DHILLON, VIK;MARSH, TOM R.
    • Publications of The Korean Astronomical Society
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    • v.30 no.2
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    • pp.201-204
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    • 2015
  • The common-envelope process is a complicated phase in binary evolution. A lot of effort has been dedicated to study the common-envelope stage, but many questions related to this process are yet to be answered. If one member of the binary survives the common-envelope phase, the binary will emerge as a white dwarf accompanied by a low-mass main sequence star in close orbit, often referred as a post common-envelope binary (PCEB). SDSS J0745+2631 is among the list of newly found PCEBs from the Sloan Digital Sky Survey (SDSS). This star is proposed to be a strong eclipsing system candidate due to the ellipsoidal modulation in its light curve. In this work, we aim to confirm the eclipsing nature of SDSS J0745+2631 and to determine the stellar and orbital parameters using the software Binary Maker 3.0 (BM3.0). We detected the primary eclipse in the light curve of SDSS J0745+2631 in our follow-up observation from January 2014 using the ULTRASPEC instrument at the Thai National Observatory. The data obtained on 7th and 8th January 2014 in g filter show an evident drop in brightness during the eclipse of the white dwarf, but this eclipse is less prominent in the data taken on the next night using a clear filter. According to our preliminary model, we find that SDSS J0745+2631 hosts a rather hot white dwarf with an effective temperature of 11500K. The companion star is a red dwarf star with a temperature of 3800K and radius of 0.3100 R. The red dwarf star almost fills its Roche lobe, causing a large ellipsoidal modulation. The mass ratio of the binary given by the Binary Maker 3.0 (BM3.0) model is M2/M1 = 0.33.

Construction of Artificial Intelligence Training Platform for Multi-Center Clinical Research (다기관 임상연구를 위한 인공지능 학습 플랫폼 구축)

  • Lee, Chung-Sub;Kim, Ji-Eon;No, Si-Hyeong;Kim, Tae-Hoon;Yoon, Kwon-Ha;Jeong, Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.10
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    • pp.239-246
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    • 2020
  • In the medical field where artificial intelligence technology is introduced, research related to clinical decision support system(CDSS) in relation to diagnosis and prediction is actively being conducted. In particular, medical imaging-based disease diagnosis area applied AI technologies at various products. However, medical imaging data consists of inconsistent data, and it is a reality that it takes considerable time to prepare and use it for research. This paper describes a one-stop AI learning platform for converting to medical image standard R_CDM(Radiology Common Data Model) and supporting AI algorithm development research based on the dataset. To this, the focus is on linking with the existing CDM(common data model) and model the system, including the schema of the medical imaging standard model and report information for multi-center research based on DICOM(Digital Imaging and Communications in Medicine) tag information. And also, we show the execution results based on generated datasets through the AI learning platform. As a proposed platform, it is expected to be used for various image-based artificial intelligence researches.

Predicting link of R&D network to stimulate collaboration among education, industry, and research (산학연 협업 활성화를 위한 R&D 네트워크 연결 예측 연구)

  • Park, Mi-yeon;Lee, Sangheon;Jin, Guocheng;Shen, Hongme;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.37-52
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    • 2015
  • The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.

Durability Evaluation by Strength due to Load Direction of Press in Common Use (상용 프레스의 하중 방향에 따른 강도에 의한 내구성 평가)

  • Cho, Jae-Ung;Han, Moon-Sik
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.12 no.6
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    • pp.52-59
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    • 2013
  • In this study, strength and durability are investigated using structural and vibration analyses on models 1 and 2 of a press in common use. Model 1 has a structure in which a punch is applied from the upper part to the lower part; however, model 2 a structure in which a punch is applied from the lower part to the upper part. Maximum displacements of models 1 and 2 are 0.018184 mm and 0.025498 mm, respectively. Maximum equivalent stresses of models 1 and 2 are 14.144 MPa and 18.58 MPa respectively. Maximum displacements are shown for the punches of both models; model 1 has less deformation than model 2. Model 1 has more durability than model 2, as determined by an investigation of the structural strength. Using natural frequency analysis, model 1 was found to have maximum deformation in the upper part of punch. Mode1 2 has its maximum deformation in the column part of the body and the upper part of the fixed pin. Using harmonic stress analysis, the maximum deformations were found on the punch part and column part of the body in the cases of models 1 and 2, respectively. As the maximum total deformation and equivalent stress in the case of model 2 are shown to become 40 times those values of model 1, the vibration durability of model 2 can be seen to be weaker than that of model 1.

Development of a Conjunctive Surface-Subsurface Flow Model for Use in Land Surface Models at a Large Scale: Part I. Model Description (대규모 육지수문모형에서 사용 가능한 지표면 및 지표하 연계 물흐름 모형의 개발: I. 모형설명)

  • Choi, Hyun-Il
    • Journal of the Korean Society of Hazard Mitigation
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    • v.8 no.2
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    • pp.59-63
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    • 2008
  • The surface runoff is one of the important components for the surface water balance. However, most Land Surface Models(LSMs), coupled to climate models at a large scale for the prediction and prevention of disasters caused by climate changes, simplistically estimate surface runoff from the soil water budget. Ignoring the role of surface flow depth on the infiltration rate causes errors in both surface and subsurface flow calculations. Therefore, for the comprehensive terrestrial water and energy cycle predictions in LSMs, a conjunctive surface-subsurface flow model at a large scale is developed by coupling a 1-D diffusion wave model for surface flow with the 3-D Volume Averaged Soil-moisture Transport(VAST) model for subsurface flow. This paper describes the new conjunctive surface-subsurface flow formulation developed for improvement of the prediction of surface runoff and spatial distribution of soil water by topography, along with basic schemes related to the terrestrial hydrologic system in Common Land Model(CLM), one of the state-of-the-art LSMs.

Development and Application of the Mode Choice Models According to Zone Sizes (분석대상 규모에 따른 수단분담모형의 추정과 적용에 관한 연구)

  • Kim, Ju-Yeong;Lee, Seung-Jae;Kim, Do-Gyeong;Jeon, Jang-U
    • Journal of Korean Society of Transportation
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    • v.29 no.6
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    • pp.97-106
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    • 2011
  • Mode choice model is an essential element for estimating- the demand of new means of transportation in the planning stage as well as in the establishment phase. In general, current demand analysis model developed for the mode choice analysis applies common parameters of utility function in each region which causes inaccuracy in forecasting mode choice behavior. Several critical problems from using common parameters are: a common parameter set can not reflect different distribution of coefficient for travel time and travel cost by different population. Consequently, the resulting model fails to accurately explain policy variables such as travel time and travel cost. In particular, the nonlinear logit model applied to aggregation data is vulnerable to the aggregation error. The purpose of this paper is to consider the regional characteristics by adopting the parameters fitted to each area, so as to reduce prediction errors and enhance accuracy of the resulting mode choice model. In order to estimate parameter of each area, this study used Household Travel Survey Data of Metropolitan Transportation Authority. For the verification of the model, the value of time by marginal rate of substitution is evaluated and statistical test for resulting coefficients is also carried out. In order to crosscheck the applicability and reliability of the model, changes in mode choice are analyzed when Seoul subway line 9 is newly opened and the results are compared with those from the existing model developed without considering the regional characteristics.

Analyzing Common Method Bias of the Korean Empirical Studies on Technology Acceptance Model (한국 TAM 실증연구의 동일방법편의 분석)

  • Baek, Sang-Yong
    • The Journal of Information Systems
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    • v.21 no.1
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    • pp.1-17
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    • 2012
  • Common Method Bias(CMB) may cause the potential inflation of correlations between measures assessed via the same method. The problem of CMB has been well known in behavioral sciences because the survey method with self-reporting is vulnerable to CMB. Thus, the discussion on CMB is still ongoing in the MIS research in US. However, in Korea, the MIS research has never paid attention on the CMB problem. The purpose of this study is to examine the CMB problem in the Korean MIS research. To evaluate the effect of CMB, empirical studies on Technology Acceptance Model(TAM) are selected because (1) TAM is one of the MIS research areas studied intensively, (2) TAM is a theoretical model well supported by the existing empirical studies so that the result of this study would have a great ripple effect when the CMB problem turned out to be serious, (3) CMB is domain-specific. 47 TAM samples (out of 45 studies) from three Korean Journals were selected and the relevant data were collected such as correlation matrixes and the measures of the dependent variable. To find and evaluate the size of CMB, two analytic methods (Marker-Variable Technique and Method-Method Pair Technique) are employed. The result showed that there exists CMB in the Korean studies but the problem is not so serious to distort the empirical testing, compared with that of US studies. However, considering that CMB can contaminate the testing results, Korean MIS researchers should explicitly deal with the problem in designing empirical studies and collecting data.

Study on Development Method of MDMS for AMI Operation based on Common Information Model (CIM 기반 AMI용 미터데이터관리시스템(MDMS) 개발 방안 연구)

  • Jung, Nam-Joon;Jin, Young-Taek;Chae, Chang-Hun;Choi, Min-Hee
    • KIPS Transactions on Computer and Communication Systems
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    • v.1 no.3
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    • pp.171-180
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    • 2012
  • In the development of MDMS(Meter Data Management System) based on CIM(Common Information Model), which is international standard in information model and data exchange on power system, the two focused issues are the effective management of data collected in a shorter time period and the way to integrate services supporting legacy system to use the AMI(AMI, Advanced Metering Infrastructure) data. In this paper, we propose MDMS implementation methods and functions in AMI environment which are differ from existing AMR system environments in that the methods support bi-directional service infrastructure. The proposed MDMS in this paper has two unique features, one is the secure of interoperability by utilizing the CIM and ESB, the other is the improvement of field application by implementing system module based on components. On an implementation of smart grid, the result of proposed methods is expected to contribute to the efficient development and operation of CIM-based power system.

A Study on Clinical Decision Support System based on Common Data Model (공통데이터모델 기반의 임상의사결정지원시스템에 관한 연구)

  • Ahn, Yoon-Ae;Cho, Han-Jin
    • Journal of the Korea Convergence Society
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    • v.10 no.11
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    • pp.117-124
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    • 2019
  • Recently, medical IT solutions are being provided on a distributed environment basis. In Korea, the necessity of developing a clinical decision support system that can share medical information in a distributed environment has been recognized and studied. The existing clinical decision support system is being built using only medical information of its own within the hospital. This makes it difficult for existing systems to achieve good results in terms of efficiency and accuracy of decision support. In order to solve these limitations, this paper proposes a design and implementation method of clinical decision support system based on common data model in medical field. To explain the application process of the proposed model, we describe the development scenario of the clinical decision support system for the diagnosis of colorectal cancer. We also propose the essential requirements for the development of successful clinical decision support systems. Through this, it is expected that it will be possible to develop clinical decision support system that can be used in various hospitals and improve the efficiency and accuracy of the system.

Effect of Choline Alfoscerate on the Progression From Mild Cognitive Impairment to Dementia: Distributed Network Analysis of a Multicenter Korean Database Using a Common Data Model

  • Jung-Min Pyun;Inho Lee;Kyungbok Lee;Min-ho Kim;ChulHyoung Park;Hyeon-Jong Yang
    • Dementia and Neurocognitive Disorders
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    • v.23 no.4
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    • pp.202-211
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    • 2024
  • Background and Purpose: Choline alfoscerate (CA) is an acetylcholine precursor known for its beneficial effect on cognition in patient with Alzheimer's disease dementia (ADD). However, there is little evidence of its effects in patients with mild cognitive impairment (MCI). We assessed the influence of CA on the progression from MCI to all-cause dementia or ADD in three observational Korean databases using a Common Data Model (CDM). Methods: Patients who were diagnosed with MCI and were aged over 60 years were included. After propensity score matching, 3,062 matched pairs patients using CA use and those not using CA were included. The Cox regression model was used to analyze the hazard ratio (HR) of CA use for conversion from MCI to all-cause dementia or ADD. Subgroup analyses were performed based on sex, acetylcholine esterase inhibitor (AchEI) use, and donepezil use. Results: A meta-analysis across three hospitals revealed that CA use was not associated with the progression from MCI to all-cause dementia (hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.59-1.26) or ADD (HR, 1.05; 95% CI, 0.51-1.59). Subgroup analyses revealed that CA use was not related to progression to all-cause dementia or ADD when stratified by sex, AchEI use, and donepezil use. Conclusions: In this multicenter cohort study based on the Observational Medical Outcomes Partnership CDM real-world data, no association was noted between CA use and disease progression from MCI to all-cause dementia or ADD.