• Title/Summary/Keyword: Count 모형

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A Study of Software Optimal Release Time for Based on Superposition NHPP Model (중첩 NHPP 모형에 근거한 소프트웨어 최적방출시기에 관한 연구)

  • Kim, Hee Cheul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.3
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    • pp.9-17
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    • 2010
  • Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used superposition which has various intensity, if the system is complicated. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time. Through this study, in terms of superposition model and simply model, the optimal time to using superposition model release the software developer to determine how much could count will help.

Developing Rear-End Collision Models of Roundabouts in Korea (국내 회전교차로의 추돌사고 모형 개발)

  • Park, Byung Ho;Beak, Tae Hun
    • Journal of the Korean Society of Safety
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    • v.29 no.6
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    • pp.151-157
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    • 2014
  • This study deals with the rear-end collision at roundabouts. The purpose of this study is to develop the accident models of rear-end collision in Korea. In pursuing the above, this study gives particular attention to developing the appropriate models using Poisson, negative binomial model, ZAM, multiple linear and nonlinear regression models, and statistical analysis tools. The main results are as follows. First, the Vuong statistics and overdispersion parameters indicate that ZIP is the most appropriate model among count data models. Second, RMSE, MPB, MAD and correlation coefficient tests show that the multiple nonlinear model is the most suitable to the rear-end collision data. Finally, such the independent variables as traffic volume, ratio of heavy vehicle, number of circulatory roadway lane, number of crosswalk and stop line are adopted in the optimal model.

Joint Modeling of Death Times and Number of Failures for Repairable Systems using a Shared Frailty Model (공유환경효과를 고려한 수리가능한 시스템의 수명과 고장회수의 결합모형 개발)

  • 박희창;이석훈
    • Journal of Korean Society for Quality Management
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    • v.26 no.4
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    • pp.111-123
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    • 1998
  • We consider the problem of modeling count data where the observation period is determined by the life time of the system under study. We assume random effects or a frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect or a frailty, the death times follow a Weibull distribution with a hazard rate. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time. A gamma distribution is assumed for the frailty model. Maximum likelihood estimators of the model parameters are obtained. A model for the time to death and the number of failures system received is constructed and consequences of the model are examined.

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A Study on the Evaluation of Economic Value of the Gulf of Mexico Recreational Red Grouper Fishery (여행비용모형 분석을 통한 유어(遊漁)활동의 경제적 가치 추정 -미국 멕시코만 Red Grouper 유어부문을 대상으로 -)

  • Kim, Do-Hoon
    • The Journal of Fisheries Business Administration
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    • v.36 no.2 s.68
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    • pp.121-134
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    • 2005
  • In order to evaluate the effectiveness of management measures and to provide policy suggestions for the allocation of total allowable catch between recreational and commercial sectors, the economic value of red grouper recreational fishery in the United States Gulf of Mexico was estimated using a Travel Cost Method(TCM), Due to the characteristic of count data, a Poisson model(PM) and a Negative binomial model(NBM) were used in the TCM. Results of models showed that the NBM was statistically more suitable than the PM since the overdispersion problem occurred in the PM. Results also indicated all signs of the estimated parameters were as expected and were significant, except for a Boat parameter in both models. Based on the results of NBM, the total economic value of the recreational red grouper fishery was estimated to be $\$698.6$ and the value per trip was $\$179.5$. In addition, the total changes in expected consumer surplus due to changes in catch rates was $ \$42.3$.

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Evaluation on the traffic count based O/D matrix using Trip Length Frequency Distribution (통행시간분포를 이용한 교통량기반 추정O/D의 신뢰성 평가에 관한 연구)

  • 이승재;손의영;김종형
    • Journal of Korean Society of Transportation
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    • v.18 no.2
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    • pp.53-62
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    • 2000
  • 현재까지 개발된 교통량 기반 O/D 추정기법들은 추정된 O/D의 신뢰성을 평가하는 기준으로 통계적 오차분석을 통한 참O/D(true O/D)와 추정O/D간의 타이를 분석하는 방법이 주류를 이루었다. 문제는 이러한 오차분석기법들이 현실적인 대규모 교통망상에 적용될 때 탐O/D를 알 수 없을 뿐만 아니라, 알 수 있다고 하더라도 추정된 O/D와의 비교 평가시에 그러한 평가방법으로 추정된 O/D의 신뢰성을 부여하기에는 많은 문제점을 가지고 있다는 점이다. 통행조사에 의한 O/D는 비록 포함되어 있는 정보가 과거의 정보라고 할지라도 현재의 통행흐름에 대하여 가장 많은 정보를 가지고 있다고 할 수 있다. 즉, 선행O/D의 정보를 크게 변화시키지 않으면서도 관측교통량으로 O/D를 추정할 수 있는 방법이 이 관점에서 매우 뛰어난 추정방법이라고 할 수 있다. 이러한 관점에서 본 연구에서는 선행O/D정보 중 통행수요예측시 가장 중요한 지표의 하나인 통행시간빈도분포 (TriP Length Frequency Distribution:TLFD)를 이용하여 추정O/D의 신뢰성 지표로 삼았다. TLFD는 4단계 모형에서 통행분포(trip distribution)시 모형을 정산하는 데 사용되는 방법으로써 죤간 통행시간을 단위별로 나누어 조사된 통행시간분포와 추정된 O/D의 통행시간분포가 유사한 지를 살피는 방법이라고 할 수 있다. 조사된 TLFD와 추정O/D의 TLFD가 유사한 모양을 이를 때 추정O/D의 신뢰성이 높다고 인정한다. 또한 TLFD는 전통적으로 조사된 표본O/D를 전 수화하는데 이용되어 그 타당성 또한 많이 검증되어 왔다. 그러나 아직까지 TLFD를 가지고 교통량으로 O/D를 추정하는 모형의 결과를 검증한 연구 결과는 없는 실정이다. 따라서, 본 연구에서는 최종적인 이러한 분석결과를 평가할 수 있을 뿐 아니라, 평가된 지표가 신뢰할 만한 수준이 아니라면, 추정된 결과를 보정할 수 있는 가능성을 제시하고자 한다.

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A Model for Analyzing Time-Varying Passengers' Crowdedness Degree of Subway Platforms Using Smart Card Data (스마트카드자료를 활용한 지하철 승강장 동적 혼잡도 분석모형)

  • Shin, Seongil;Lee, Sangjun;Lee, Changhun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.5
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    • pp.49-63
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    • 2019
  • Crowdedness management at subway platforms is essential to improve services, including the prevention of train delays and ensuring passenger safety. Establishing effective crowdedness mitigation measures for platforms requires accurate estimation of the congestion level. There are temporal and spatial constraints since crowdedness on subway platforms is assessed at certain locations every 1-2 years by hand counting. However, smart cards generate real-time big data 24 hours a day and could be used in estimating congestion. This study proposes a model based on data from transit cards to estimate crowdedness dynamically. Crowdedness was defined as demand, which can be translated into passengers dynamically moving along a subway network. The trajectory of an individual passenger can be identified through this model. Passenger flow that concentrates or disperses at a platform is also calculated every minute. Lastly, the platform congestion level is estimated based on effective waiting areas for each platform structure.

A Machine Learning-based Popularity Prediction Model for YouTube Mukbang Content (머신러닝 기반의 유튜브 먹방 콘텐츠 인기 예측 모델)

  • Beomgeun Seo;Hanjun Lee
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.49-55
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    • 2023
  • In this study, models for predicting the popularity of mukbang content on YouTube were proposed, and factors influencing the popularity of mukbang content were identified through post-analysis. To accomplish this, information on 22,223 pieces of content was collected from top mukbang channels in terms of subscribers using APIs and Pretty Scale. Machine learning algorithms such as Random Forest, XGBoost, and LGBM were used to build models for predicting views and likes. The results of SHAP analysis showed that subscriber count had the most significant impact on view prediction models, while the attractiveness of a creator emerged as the most important variable in the likes prediction model. This confirmed that the precursor factors for content views and likes reactions differ. This study holds academic significance in analyzing a large amount of online content and conducting empirical analysis. It also has practical significance as it informs mukbang creators about viewer content consumption trends and provides guidance for producing high-quality, marketable content.

Usefulness Evaluation of Artifacts by Bone Cement of Percutaneous Vertebroplasty Performed Patients and CT Correction Method in Spine SPECT/CT Examinations (척추 뼈 SPECT/CT검사에서 경피적 척추성형술 시행 환자의 골 시멘트로 인한 인공물과 CT보정방법의 유용성 평가)

  • Kim, Ji-Hyeon;Park, Hoon-Hee;Lee, Juyoung;Nam-Kung, Sik;Son, Hyeon-Soo;Park, Sang-Ryoon
    • The Korean Journal of Nuclear Medicine Technology
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    • v.18 no.1
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    • pp.49-61
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    • 2014
  • Purpose: With the aging of the population, the attack rate of osteoporotic vertebral compression fracture is in the increasing trend, and percutaneous vertebroplasty (PVP) is the most commonly performed standardized treatment. Although there is a research report of the excellence of usefulness of the SPECT/CT examination in terns of the exact diagnosis before and after the procedure, the bone cement material used in the procedure influences the image quality by forming an artifact in the CT image. Therefore, the objective of the research lies on evaluating the effect the bone cement gives to a SPECT/CT image. Materials and Methods: The images were acquired by inserting a model cement to each cylinder, after setting the background (3.6 kBq/mL), hot cylinder (29.6 kBq/mL) and cold cylinder (water) to the NEMA-1994 phantom. It was reconstructed with Astonish (Iterative: 4 Subset: 16), and non attenuation correction (NAC), attenuation correction (AC+SC-) and attenuation and scatter correction (AC+SC+) were used for the CT correction method. The mean count by each correction method and the count change ratio by the existence of the cement material were compared and the contrast recovery coefficient (CRC) was obtained. Additionally, the bone/soft tissue ratio (B/S ratio) was obtained after measuring the mean count of the 4 places including the soft tissue(spine erector muscle) after dividing the vertebral body into fracture region, normal region and cement by selecting the 20 patients those have performed PVP from the 107 patients diagnosed of compression fracture. Results: The mean count by the existence of a cement material showed the rate of increase of 12.4%, 6.5%, 1.5% at the hot cylinder of the phantom by NAC, AC+SC- and AC+SC+ when cement existed, 75.2%, 85.4%, 102.9% at the cold cylinder, 13.6%, 18.2%, 9.1% at the background, 33.1%, 41.4%, 63.5% at the fracture region of the clinical image, 53.1%, 61.6%, 67.7% at the normal region and 10.0%, 4.7%, 3.6% at the soft tissue. Meanwhile, a relative count reduction could be verified at the cement adjacent part at the inside of the cylinder, and the phantom image on the lesion and the count increase ratio of the clinical image showed a contrary phase. CRC implying the contrast ratio and B/S ratio was improved in the order of NAC, AC+SC-, AC+SC+, and was constant without a big change in the cold cylinder of the phantom. AC+SC- for the quantitative count, and AC+SC+ for the contrast ratio was analyzed to be the highest. Conclusion: It is considered to be useful in a clinical diagnosis if the application of AC+SC+ that improves the contrast ratio is combined, as it increases the noise count of the soft tissue and the scatter region as well along with the effect of the bone cement in contrast to the fact that the use of AC+SC- in the spine SPECT/CT examination of a PVP performed patient drastically increases the image count and enables a high density of image of the lesion(fracture).

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Physical Properties and Sensibility on the Transformed Colors from the Rustling Sounds of Fabrics (견직물의 스치는 소리로부터 변환된 색채의 물리량과 감성)

  • 김춘정;최계연;김수아;조길수
    • Science of Emotion and Sensibility
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    • v.5 no.1
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    • pp.25-32
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    • 2002
  • This paper aimed to identify the sensation and the sensibility of transformed colors from the rustling sound of silk fabrics and to visualize the relationship between sensibilities and fabrics by two-dimensional model. The rustling sounds of 7 silk fabrics were recorded and then the recorded sounds were transformed into colors by the program of sound to color transformation. The sensation and the sensibility of transformed colors were evaluated by 30 participants with Likert scale and the physical properties of each specimen were obtained with red portion (RP), green portion (GP), blue portion (BP), and sum of color count (CC) by means of new equation. The adjectives of sensibility were grouped into three groups: Elegant, Active, and Tough. Elegant was related with RP positively and CC negatively. On the other hand, Active was related with GP and CC positively. Also Tough was highly related with RP. Furthermore, the fabrics that were estimated the high purchase preference showed high CC, RP and GP. Also two dimensional model of relation of the sensation and the sensibility could help to understand those relation.

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Mixed-effects zero-inflated Poisson regression for analyzing the spread of COVID-19 in Daejeon (혼합효과 영과잉 포아송 회귀모형을 이용한 대전광역시 코로나 발생 동향 분석)

  • Kim, Gwanghee;Lee, Eunjee
    • The Korean Journal of Applied Statistics
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    • v.34 no.3
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    • pp.375-388
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    • 2021
  • This paper aims to help prevent the spread of COVID-19 by analyzing confirmed cases of COVID-19 in Daejeon. A high volume of visitors, downtown areas, and psychological fatigue with prolonged social distancing were considered as risk factors associated with the spread of COVID-19. We considered the weekly confirmed cases in each administrative district as a response variable. Explanatory variables were the number of passengers getting off at a bus station in each administrative district and the elapsed time since the Korean government had imposed distancing in daily life. We employed a mixed-effects zero-inflated Poisson regression model because the number of cases was repeatedly measured with excess zero-count data. We conducted k-means clustering to identify three groups of administrative districts having different characteristics in terms of the number of bars, the population size, and the distance to the closest college. Considering that the number of confirmed cases might vary depending on districts' characteristics, the clustering information was incorporated as a categorical explanatory variable. We found that Covid-19 was more prevalent as population size increased and a district is downtown. As the number of passengers getting off at a downtown district increased, the confirmed cases significantly increased.