• 제목/요약/키워드: Network characteristic variables

검색결과 62건 처리시간 0.023초

Robustness Analysis Under Second-Order Plant and Delay Uncertainties for Symmetrically Coupled Systems with Time Delay

  • Cheong Joon-O;Kwon Sang-Joo
    • Journal of Mechanical Science and Technology
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    • 제20권8호
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    • pp.1195-1208
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    • 2006
  • This paper aims at presenting robustness analysis under the uncertainties of the time delay and plant parameters in symmetrically coupled dynamic systems connected through network having time delay. The delay-involved closed loop characteristic function is mathematically formulated, incorporated with active synchronization control. And the robust stability of the corresponding system is analyzed by investigating the formation of characteristic equation containing second- order terms of uncertainty variables representing delay and plant dynamics mismatches. For the two individual types of uncertainties, we elucidate details of how to compute the bounds and what they imply physically. To support the validity of the mathematical claims, numerical examples and simulations are presented.

사이트 품질, 개인적 특성 및 관계 혜택이 관계 품질을 매개로 소셜네트워크서비스 지속사용의도에 미치는 영향 (The Effects of Site Quality, Personal Characteristic, and Relationship Benefit on the Continuance Intention to Use Social Network Services through Relationship Quality)

  • 허현정;박경배;노미진
    • 한국정보시스템학회지:정보시스템연구
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    • 제24권1호
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    • pp.67-94
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    • 2015
  • Recently, the popularity of Social Network Service (SNS) along with the spread of smart phone, personal computer and tablet PC helps personal network to construct new forms of services in cyberspace. As such, SNS plays a significant role in constructing diverse online networks and there is a growing interest on SNS at societal level. In this vein, the purpose of the research was to find the factors affecting the continuance intention to use social network services. The major findings are summarized as follows. First, "System Quality", "Contents Quality", "Personal Innovativeness", "Self-Efficiency", "Honor Benefit" has significant effects on "Relationship Quality". Yet, "Economic Benefit" is not statistically significant on "Relationship Quality". Second, "Relationship Quality" has a significant effect on "Continuous Usage Intention". Last, our research discovered the relationship between exogenous variables which would serve as valuable inputs in the development of strategic guideline and plan for SNS companies and related services.

WSN 노드 이동 환경에서 stochastic 모델 설계 (Stochastic Mobility Model Design in Mobile WSN)

  • 윤대열;윤창표;황치곤
    • 한국정보통신학회논문지
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    • 제25권8호
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    • pp.1082-1087
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    • 2021
  • 노드 이동 모델은 활용 서비스 및 목적에 따라 제안되어야 한다. 현재 가장 널리 활용되는 무작위 이동 모델은 간편하고 구현하기가 쉽다는 장점이 있다. 이 모델에서 노드 이동 특성은 이동 속도와 이동 방향을 무작위 속성으로 처리하며, 매번 노드들의 이동이 서로 독립적으로 발생한다. 본 논문에서는 모바일 애드혹 네트워크 이동 환경에서 적용 가능한 확률론적인 이동 모델을 제안한다. 제안 확률 이동 모델에서는 네트워크의 전체 노드 이동 특성을 표현하기 위하여 이동하는 노드 수와 노드 이동 거리가 특정 확률 분포 특성을 가지도록 랜덤 변수로 처리한다. 또한, 제안 이동 모델을 대표적인 무작위 이동 모델과 비교하여 노드들의 이동 변화에 안정적인 특성을 나타냄을 보이고, 기존 라우팅 프로토콜에 제안 모델을 적용하여 에너지 소비 효율 측면에서 향상된 특성을 보임을 확인한다.

원형봉에서 사각재 인발 공정의 코너 채움에 관한 연구 (A Study on the Corner Filling in the Drawing of Quadrangle Rod from Round Bar)

  • 김용철;김동진;김병민
    • 한국정밀공학회지
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    • 제17권6호
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    • pp.143-152
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    • 2000
  • The comer filling in shaped drawing process is an important characteristic, unlike the round drawing. It has also influence on the dimensional accuracy of the product. In this study, therefore, the shaped drawing process has been simulated by the three dimensional rigid-plastic finite element method in order to investigate the effect of process variables such as reduction in area and semi-die angle to the corner filling. The artificial neural network has also been introduced to reduce the number of simulations. To verify the results of simulations, experiments have been performed on the real industrial products. According to the results, the main process variable on the corner filling is the combination of semi-die angle in the irregular shaped drawing processes, but in the case of regular shaped drawing processes, reduction in area has great influence on the corner filling.

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Use of an Artificial Neural Network to Predict Risk Factors of Nosocomial Infection in Lung Cancer Patients

  • Chen, Jie;Pan, Qin-Shi;Hong, Wan-Dong;Pan, Jingye;Zhang, Wen-Hui;Xu, Gang;Wang, Yu-Min
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권13호
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    • pp.5349-5353
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    • 2014
  • Statistical methods to analyze and predict the related risk factors of nosocomial infection in lung cancer patients are various, but the results are inconsistent. A total of 609 patients with lung cancer were enrolled to allow factor comparison using Student's t-test or the Mann-Whitney test or the Chi-square test. Variables that were significantly related to the presence of nosocomial infection were selected as candidates for input into the final ANN model. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. The prevalence of nosocomial infection from lung cancer in this entire study population was 20.1% (165/609), nosocomial infections occurring in sputum specimens (85.5%), followed by blood (6.73%), urine (6.0%) and pleural effusions (1.82%). It was shown that long term hospitalization (${\geq}22days$, P= 0.000), poor clinical stage (IIIb and IV stage, P=0.002), older age (${\geq}61days$ old, P=0.023), and use the hormones were linked to nosocomial infection and the ANN model consisted of these four factors. The artificial neural network model with variables consisting of age, clinical stage, time of hospitalization, and use of hormones should be useful for predicting nosocomial infection in lung cancer cases.

기상레이더를 이용한 뉴로-퍼지 알고리즘 기반 강수/비강수 패턴분류 시스템 설계 : 사례 분류기 및 에코 분류기 (Design of Precipitation/non-precipitation Pattern Classification System based on Neuro-fuzzy Algorithm using Meteorological Radar Data : Instance Classifier and Echo Classifier)

  • 고준현;김현기;오성권
    • 전기학회논문지
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    • 제64권7호
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    • pp.1114-1124
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    • 2015
  • In this paper, precipitation / non-precipitation pattern classification of meteorological radar data is conducted by using neuro-fuzzy algorithm. Structure expression of meteorological radar data information is analyzed in order to effectively classify precipitation and non-precipitation. Also diverse input variables for designing pattern classifier could be considered by exploiting the quantitative as well as qualitative characteristic of meteorological radar data information and then each characteristic of input variables is analyzed. Preferred pattern classifier can be designed by essential input variables that give a decisive effect on output performance as well as model architecture. As the proposed model architecture, neuro-fuzzy algorithm is designed by using FCM-based radial basis function neural network(RBFNN). Two parts of classifiers such as instance classifier part and echo classifier part are designed and carried out serially in the entire system architecture. In the instance classifier part, the pattern classifier identifies between precipitation and non-precipitation data. In the echo classifier part, because precipitation data information identified by the instance classifier could partially involve non-precipitation data information, echo classifier is considered to classify between them. The performance of the proposed classifier is evaluated and analyzed when compared with existing QC method.

다변량기법을 활용한 용담호 수질측정지점 유사성 연구 (A Study on Measuring the Similarity Among Sampling Sites in Lake Yongdam with Water Quality Data Using Multivariate Techniques)

  • 이요상;권세혁
    • 환경영향평가
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    • 제18권6호
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    • pp.401-409
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    • 2009
  • Multivariate statistical approaches to classify sampling sites with measuring their similarity by water quality data and understand the characteristics of classified clusters have been discussed for the optimal water quality monitering network. For empirical study, data of two years (2005, 2006) at the 9 sampling sites with the combination of 2 depth levels and 7 important variables related to water quality is collected in Yongdam reservoir. The similarity among sampling sites is measured with Euclidean distances of water quality related variables and they are classified by hierarchical clustering method. The clustered sites are discussed with principal component variables in the view of the geographical characteristics of them and reducing the number of measuring sites. Nine sampling sites are clustered as follows; One cluster of 5, 6, and 7 sampling sites shows the characteristic of low water depth and main stream of water. The sites of 2 and 4 are clustered into the same group by characteristics of hydraulics which come from that of main stream. But their changing pattern of water quality looks like different since the site of 2 is near to dam. The sampling sites of 3, 8, and 9 are individually positioned due to the different tributary.

The Effect of Perceived Risk, Hedonic Value, andSelf-Construal on Attitude toward Mobile SNS

  • Kim, Ji Yoon;Kim, Sang Yong
    • Asia Marketing Journal
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    • 제16권1호
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    • pp.149-168
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    • 2014
  • This study investigates the effect of perceived risk on attitude toward mobile Social Network Services (SNSs). First, we understand that perceived risk of SNSs is a multidimensional concept, and we study the relationship between attitude and perceived risk such as social risk, performance risk, and privacy risk in SNS environments. Subsequently, the relationships between these multidimensional concepts of perceived risk and attitude are investigated. The result indicates that social, performance, and privacy risk have negative effects on attitude. In addition, the moderated effect of individual characteristic variables such as hedonic value and self-construal are confirmed as mitigating factors that alleviate the negative impact of perceived risk. The Findings show that customers who perceive SNSs to be risky are more likely to have a negative attitude toward SNSs. However, the negative impact of perceived risk on their attitude toward SNSs is alleviated in customers with high hedonic value. Similarly, the negative impact of perceived risk on their attitude toward SNS is weaker with customers in interdependent self-construal. This paper presents effective segmentation variables, such as consumer's motivation (hedonic value) and psychological variable (self-construal), which mitigate the risk perception of customers. Therefore, it provides practical guidelines for the marketing managers in terms of who to target and what kind of strategies to implement in terms of these segmentation variables to approach consumers more efficiently.

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터빈 블레이드 냉각시스템에 관한 수치해석적 연구 (NUMERICAL STUDY OF TURBINE BLADE COOLING TECHNIQUES)

  • 김광용;이기돈;문미애;허만웅;김현민;김진혁
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2010년 춘계학술대회논문집
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    • pp.530-533
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    • 2010
  • This paper presents numerical analysis and design optimization of various turbine blade cooling techniques with three-dimensional Reynolds-averaged Navier-Stokes(RANS) analysis. The fluid flow and heat transfer have been performed using ANSYS-CFX 11.0. A fan-shaped hole for film-cooling has been carried out to improve film-cooling effectiveness with the radial basis neural network method. The injection angle of hole, lateral expansion angle of hole and ratio of length-to-diameter of the hole are chosen as design variables and spatially averaged film-cooling effectiveness is considered as an objective function which is to be maximized. The impingement jet cooling has been performed to investigate heat transfer characteristic with geometry variables. Distance between jet nozzle exit and impingement plate, inclination of nozzle and aspect ratio of nozzle hole are considered as geometry variables. The area averaged Nusselt number is evaluated each geometry variables. A rotating rectangular channel with staggered array pin-fins has been investigated to increase heat transfer performance ad to decrease friction loss using KRG modeling. Two non-dimensional variables, the ratio of the eight diameter of the pin-fins and ratio of the spacing between the pin-fins to diameter of the pin-fins selected as design variables. A rotating rectangular channel with staggered dimples on opposite walls are formulated numerically to enhance heat transfer performance. The ratio of the dimple depth and dimple diameter are selected as geometry variables.

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양식뱀장어 생산단계 안전성 조사를 위한 베이지안 네트워크 모델의 적용 (Application of Bayesian network for farmed eel safety inspection in the production stage)

  • 조승용
    • 한국식품저장유통학회지
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    • 제30권3호
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    • pp.459-471
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    • 2023
  • 뱀장어 생산단계 안전성조사 부적합여부에 영향을 미치는 특성변수를 베이지안 네트워크(BN) 모델을 적용하여 분석하였다. 2012년부터 2021년까지의 통합식품안전정보망(IFSIN)의 뱀장어 생산단계 안전성조사 데이터에 양식장의 HACCP 정보, 지리적 정보 및 용수환경 데이터를 연계하여 BN 모델을 수립하였다. 뱀장어의 부적합여부에 영향을 주는 특성변수로 양식장의 HACCP 인증여부, 양식장의 이전 5년간 검사대상 유해물질의 검출여부, 해당 양식장의 이전 5년간 부적합적발이력, 사용되는 용수환경의 적정성이 제안되었으며, 이때 용수환경의 적정성은 총대장균군과 총유기탄소량으로부터 산출되었다. 뱀장어 부적합이 발생할 확률이 가장 높은 경우는 지난 5년간 검사대상 유해물질의 검출이력이 있으면서 동시에 부적합 적발 이력이 있는 HACCP 인증을 받지 않은 양식장으로서, 용수환경도 총대장균군 또는 총유기탄소가 높아 오염이 의심되는 용수를 사용하는 경우로 이때 부적합이 발생할 확률은 24.5%로 뱀장어 생산단계 안전성 조사 시 부적합률인 0.26%의 94배 높았다. 2022년 1월부터 8월까지 뱀장어 양식장 안전성조사 결과를 시험용 데이터세트(6,785건 중 부적합 15건)로 하여 BN 모델의 적정성을 검토하였다. 영향강도가 높았던 설명변수인 HACCP, 검출이력, 부적합이력으로 구성한 BN 모델을 시험용 데이터세트에 적용한 결과 부적합일 확률이 15.8%로 시험용데이터의 부적합률인 0.22%의 약 71.4배 개선할 수 있었다. 그러나 이 모델의 재현율은 0.2에 머물렀는데, 이는 특히 부적합항목인 유해물질의 기준·규격이 신설되어 해당 양식장에서 검사기록이 없는 경우와, 매우 드물게 발생하여 10년 동안 검출이력이 없어 학습데이터세트에는 없는 경우이었다. 베이지안 네트워크를 적용하여 부적합확률이 높은 생산단계 안전성 조사대상을 선정하게 되면 설명변수별로 시나리오에 따라 부적합확률을 설명가능하게 되어 다른 머신러닝 알고리즘을 적용하는 경우 지적되어온 설명불가능이라는 문제점을 해소할 수 있으며, 향후 안전성조사 데이터 축적 시 용이하게 모델 업데이트가 가능하며 이를 통해 모델의 예측성능개선도 기대할 수 있다는 장점이 있다.