• 제목/요약/키워드: Success Models

검색결과 472건 처리시간 0.025초

Analysis of Success Factors of Electric Scooter Sharing Service Using User Review Text Mining

  • Kyoung-ae Seo;Jung Seung Lee
    • Journal of Information Technology Applications and Management
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    • 제30권2호
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    • pp.19-30
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    • 2023
  • This study aims to analyze service improvement and success factors of electric scooter sharing service companies by using text mining after collecting reviews of shared electric scooter service applications among various models of sharing economy. In this study, the factors of satisfaction and dissatisfaction of service users were identified using the term frequency inverse document frequency (TF-IDF) technique, and topics for each keyword were extracted using the Latent Dirichlet Allocation (LDA) Topic Modeling technique. According to the analysis results, the main topics were entertainment, safety, service area, application complaints, use complaints, convenience, and mobility. Using the analysis results of this study, employees and researchers of electric scooter sharing service companies will be able to contribute to the improvement and success of related services.

베이지안 기법을 적용한 우주발사체의 발사 성공률 추정에 관한 연구 (A Study on the Estimation of Launch Success Probability for Space Launch Vehicles Using Bayesian Method)

  • 유승우;김인걸
    • 한국항공우주학회지
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    • 제48권7호
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    • pp.537-546
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    • 2020
  • 우주발사체 개발과정에서 설계와 프로세스의 성능지표로 활용되는 신뢰도는 발사 성공률로 유효성이 확인되고, 반복된 발사를 통해 수집된 데이터는 신뢰도 관리를 위하여 피드백 되어야 한다. 본 논문에서는 전 세계 우주발사체의 발사 이력을 조사하여 발사체 모델이나 발사 운용을 통한 기술 성숙도에 따른 발사 성공률을 비교 분석하였고, 사전정보를 반영한 사전확률분포에 발사를 통해 관측된 데이터를 업데이트하는 베이지안 기법을 적용하여 다음 발사에서 예상되는 성공률을 추정하였다. 여러 유형의 사전확률분포를 사용하여 추정한 발사 성공률과 전통적인 통계 기법을 통해 산출한 성공률을 비교 분석하여 적절한 사전분포를 설정하는 방안을 검토하였고, 베이지안 기법을 적용하여 미래의 발사 성공률을 예측하기 위해 고려할 사항들을 제시하였다.

인터넷 비즈니스 모델 개발 전략 (The Strategy for Developing Internet Business Models)

  • 주재훈
    • 한국정보시스템학회지:정보시스템연구
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    • 제10권2호
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    • pp.33-64
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    • 2001
  • With the development of the Internet, electronic commerce, electronic markets, and digital economy, new business paradigm and new ways of business have been emerging and developing. The development of right and robust business models for electronic markets is a key for Internet business success. This parer reviews previous studies and successful cases for business models based on the Internet. This paper presents strategic factors such as the business value and the source of revenue, products and services, business processes and technologies, and the characteristics of electronic markets and relationship with customers and partners as a framework for developing sustainable and robust business models. This paper presents seven propositions for developing successful Internet business models as guidelines for practitioners and theorists.

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Genetically Engineered Mouse Models for Drug Development and Preclinical Trials

  • Lee, Ho
    • Biomolecules & Therapeutics
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    • 제22권4호
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    • pp.267-274
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    • 2014
  • Drug development and preclinical trials are challenging processes and more than 80% to 90% of drug candidates fail to gain approval from the United States Food and Drug Administration. Predictive and efficient tools are required to discover high quality targets and increase the probability of success in the process of new drug development. One such solution to the challenges faced in the development of new drugs and combination therapies is the use of low-cost and experimentally manageable in vivo animal models. Since the 1980's, scientists have been able to genetically modify the mouse genome by removing or replacing a specific gene, which has improved the identification and validation of target genes of interest. Now genetically engineered mouse models (GEMMs) are widely used and have proved to be a powerful tool in drug discovery processes. This review particularly covers recent fascinating technologies for drug discovery and preclinical trials, targeted transgenesis and RNAi mouse, including application and combination of inducible system. Improvements in technologies and the development of new GEMMs are expected to guide future applications of these models to drug discovery and preclinical trials.

Comparison of Empirical Magnetopause Location Models with Geosynchronous Satellite Data

  • Park, Eunsu;Moon, Yong-Jae
    • 천문학회보
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    • 제41권1호
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    • pp.44.3-45
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    • 2016
  • In this study, we identify 307 the geosynchronous magnetopause crossing (GMC) using geosynchronous satellite observation data from 1996 to 2010 as well as make an observational test of magnetopause location models using the identified events. For this, we consider three models: Petrinec and Russell (1996), Shue et al. (1998), and Lin et al. (2010). To evaluate the models, we estimate a Probability of Detection (PoD) and a Critical Success Index (CSI) as a function of year. To examine the effect of solar cycle phase, we consider three different time periods: (1) ascending phase (1996-1999), (2) maximum phase (2000-2002), and (3) descending phase (2003-2008). Major results from this study are as follows. First, the PoD values of all models range from 0.6 to 1.0 for the most of years. Second, the PoD values of Lin et al. (2010) are noticeably higher than those of the other models. Third, the CSI values of all models range from 0.3 to 0.6 and those of Shue et al. (1998) are slightly higher than those of the other models. Fourth, the predicted magnetopause radius based on Lin et al.(2010) well match the observed one within one earth radius, while that on Shue et al. (1998) overestimate the observed one by about 2 earth radii. Fifth, the PoD and CSI values of all the models are better for the solar maximum phase than those for the other phases, implying that the models are more optimized for the phase.

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A within-subject comparison of short implants in the posterior region: retrospective study of up to 10 years

  • Segalla, Douglas Blum;Villarinho, Eduardo Aydos;Correia, Andre Ricardo Maia;Vigo, Alvaro;Shinkai, Rosemary Sadami Arai
    • The Journal of Advanced Prosthodontics
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    • 제13권3호
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    • pp.172-179
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    • 2021
  • Purpose. This intra-patient retrospective study of up to 10 years evaluated the clinical success and risk factors of 6- and 8-mm long implants and their respective prostheses. Materials and Methods. The sample consisted of patients treated at a Military Polyclinic dental service, who received both 6- and 8-mm long tissue level implants in the posterior region of the same arch. Data were collected from the dental charts, clinical and radiographic exams, self-report of sleep bruxism, measurement of maximum occlusal force, and clinical crown-to-implant (C/I) ratio. Data were analyzed by descriptive and inferential statistics with univariate and hierarchical multivariate models, at the 0.05 significance level. Results. The 30 patients (27 women) had 85 implants and 83 prostheses. Two implants were lost before prosthesis installation (implant survival: 97.6%). Ten events of prosthetic complication (screw tightening loss) occurred in five patients (success rate: 87.9%) in a single moment. Only the variable C/I ratio had a significant effect for repairable prosthesis complication (P<.05). Conclusion. The results suggest that 6- and 8-mm long implants have similar long-term clinical success for implants and prostheses.

Prediction of concrete spall damage under blast: Neural approach with synthetic data

  • Dauji, Saha
    • Computers and Concrete
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    • 제26권6호
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    • pp.533-546
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    • 2020
  • The prediction of spall response of reinforced concrete members like columns and slabs have been attempted by earlier researchers with analytical solutions, as well as with empirical models developed from data generated from physical or numerical experiments, with different degrees of success. In this article, compared to the empirical models, more versatile and accurate models are developed based on model-free approach of artificial neural network (ANN). Synthetic data extracted from the results of numerical experiments from literature have been utilized for the purpose of training and testing of the ANN models. For two concrete members, namely, slabs and columns, different sets of ANN models were developed, each of which proved to have definite advantages over the corresponding empirical model reported in literature. In case of slabs, for all three categories of spall, the ANN model results were superior to the empirical models as evaluated by the various performance metrics, such as correlation, root mean square error, mean absolute error, maximum overestimation and maximum underestimation. The ANN models for each category of column spall could handle three variables together: namely, depth, spacing of longitudinal and transverse reinforcement, as contrasted to the empirical models that handled one variable at a time, and at the same time yielded comparable performance. The application of the ANN models for spall prediction of concrete slabs and columns developed in this study has been discussed along with their limitations.

A neural network model for predicting atlantic hurricane activity

  • Kwon, Ohseok;Golden, Bruce
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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    • pp.39-42
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    • 1996
  • Modeling techniques such as linear regression have been used to predict hurricane activity many months in advance of the start of the hurricane season with some success. In this paper, we construct feedforward neural networks to model Atlantic basin hurricane activity and compare the predictions of our neural network models to the predictions produced by statistical models found in the weather forecasting literature. We find that our neural network models produce reasonably accurate predictions that, for the most part, compare favorably to the predictions of statistical models.

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객체 탐지 과업에서의 트랜스포머 기반 모델의 특장점 분석 연구 (A Survey on Vision Transformers for Object Detection Task)

  • 하정민;이현종;엄정민;이재구
    • 대한임베디드공학회논문지
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    • 제17권6호
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    • pp.319-327
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    • 2022
  • Transformers are the most famous deep learning models that has achieved great success in natural language processing and also showed good performance on computer vision. In this survey, we categorized transformer-based models for computer vision, particularly object detection tasks and perform comprehensive comparative experiments to understand the characteristics of each model. Next, we evaluated the models subdivided into standard transformer, with key point attention, and adding attention with coordinates by performance comparison in terms of object detection accuracy and real-time performance. For performance comparison, we used two metrics: frame per second (FPS) and mean average precision (mAP). Finally, we confirmed the trends and relationships related to the detection and real-time performance of objects in several transformer models using various experiments.

Feature Analysis for Seceders among New Students Passed the D University Entrance Examination

  • Choi, Seung-Bae;Kang, Chang-Wan;Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • 제19권4호
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    • pp.1111-1122
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    • 2008
  • Recently, because of decreasing in population, most of local universities are competing to attract new students in the entrance examination. These situations cause that most of the examinee apply for several universities to matriculate in a university. So these problem may raise a serious trouble such as additional new students invited. Therefore, in this study, we consider a few statistical models by using data mining technique to understand the pattern of new students who discard registration(seceders) in spite of success in the D university entrance examination. To construct these models, we use entrance examination data of three years. On the basis for analysis results of entrance examination data, we look into the features for secession of new students who success in an university entrance examination. We provide a basic information to make a effective entrance plan for seceders in future. Also, we make a search for the trend based on three years by analyzing entrance examination data of 2006, 2007 and 2008 years.

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