• 제목/요약/키워드: predictive tools

검색결과 116건 처리시간 0.022초

Predictive Research into Desirable Features of Machine Tools in the Year 2015 and Beyond - Private Viewpoints and Assertion -

  • Yos
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 Handout for 2000 Inter. Machine Tool Technical Seminar
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    • pp.1-18
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    • 2000
  • This paper describes firstly a prediction for desirable features of the machine tool in the year 2015 and beyond, and then delineates something definite in relation to some representative machine tools, which could be realised in very near future. The paper depicts furthermore another aspect of future machine tools, I. e., innovative structural designs. In addition, author asserts the importance of grass root-like knowledge, when predicting the desirable feature of machine tools future together with showing some evidences.

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Predictive analysis in insurance: An application of generalized linear mixed models

  • Rosy Oh;Nayoung Woo;Jae Keun Yoo;Jae Youn Ahn
    • Communications for Statistical Applications and Methods
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    • 제30권5호
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    • pp.437-451
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    • 2023
  • Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

병원간접원가의 예측수단으로서의 회귀식 모형과 인공신경망 모형에 대한 비교연구 (A Comparison of the Regression and Neural Network as Predictive Tools of the Overhead Costs in Hospitals)

  • 양동현;박광훈;김선민
    • 한국병원경영학회지
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    • 제4권2호
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    • pp.354-368
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    • 1999
  • This research aims to compare between regression and neural network in terms of the predictive ability of the overhead costs in hospitals. For this purpose, this research uses the number of out-patients and complex medical treatments as explaining variables. Thirty-one hospitals were used for the empirical test The test result shows that the regression model has a more predictive ability than the neural network.

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IC 설계용 집적형 캐드 시스템의 구현 (An Implementation of integrated CAD system of IC design)

  • 공진흥;김성중;김재협
    • 전자공학회논문지A
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    • 제30A권1호
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    • pp.73-85
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    • 1993
  • This paper presents a design and implementation of CAD(Computer-Aided Design) system with tools and design environments for IC(Intergrated Circuits)design. The CAD system can be easily installed in various sites with limited resources, since most CAD tools and design environments are available in the public-domain and Unix & X Window-based PC-386 and Workstation is used for the hardware platform. In order to improve the flexibility of the CAD system, objects are defined in the context of tools and environments` and object tables are programmed to describe the integration of CAD tools and design environments. During the execution, tool-objects deal with intertool communication and round-robin mechanism to incrementally control the execution of CAD tools. The IC design of LPC(Linear Predictive Coding) Speech Synthesizer is carried out to find out improvements and bugs of the CAD system.

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후향적 자료분석을 통한 낙상위험 사정도구의 타당도 비교: 종합병원 입원 환자를 중심으로 (Validation of Fall Risk Assessment Scales among Hospitalized Patients in South Korea using Retrospective Data Analysis)

  • 강영옥;송라윤
    • 성인간호학회지
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    • 제27권1호
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    • pp.29-38
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    • 2015
  • Purpose: The purpose of the study was to validate fall risk assessment scales among hospitalized adult patients in South Korea using the electronic medical records by comparing sensitivity, specificity, positive predictive values, and negative predictive values of Morse Fall Scale (MFS), Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS), and Johns Hopkins Hospital Fall Risk Assessment tool (JHFRAT). Methods: A total of 120 patients who experienced fall episodes during their hospitalization from June 2010 to December 2013 was categorized into the fall group. Another 120 patients, who didn't experience fall episodes with age, sex, clinical departments, and the type of wards matched with the fall group, were categorized to the comparison group. Data were analyzed for the comparisons of sensitivity, specificity, positive and negative predictive values, and the area under the curve of the three tools. Results: MFS at a cut-off score of 48 had .806 for ROC curves, 76.7% for sensitivity, 77.5% for specificity, 77.3% for positive predictive value, and 76.9% for negative predictive value, which were the highest values among the three fall assessment scales. Conclusion: The MFS with the highest score and the highest discrimination was evaluated to be suitable and reasonable for predicting falls of inpatients in med-surg units of university hospitals.

H.264의 가변 블록 크기 움직임 추정 및 공간 예측 부호화 생략에 의한 고속 모드 결정법 (Fast mode decision by skipping variable block-based motion estimation and spatial predictive coding in H.264)

  • 한기훈;이영렬
    • 대한전자공학회논문지SP
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    • 제40권5호
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    • pp.417-425
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    • 2003
  • ITU-T(International Telecommunication Union-Telecommunication standardization sector)와 MPEG(Moving Picture Experts Group)에 의해서 최근 표준화가 완성된 H.264는 가변 블록 크기 움직임 추정, 복수참조영상, 1/4화소 움직임 예측/보상, 4×4 정수 DCT(Integer Discrete Cosine Transform), 율-왜곡 최적화(Rate-Distortion Optimization) 등의 새로운 부호화 기술로 H.263, MPEG-4 등 기존 비디오 표준에 비해 더 좋은 부호화 효율을 제공하고 있다. 그러나 새로운 부호화 기술들은 H.264 의 전반적인 복잡도를 심화시키는 주된 요인이기도 하다. 따라서, H.254 의 실제 응용을 용이하게 하기 위해서는 이러한 기술에 대한 고속 알고리즘이 요구된다. 본 논문에서는 율-왜곡 최적화를 통한 부호화 모드 결정시 부호화기의 복잡도에서 가장 큰 비중을 차지하는 가변 블록 크기 움직임 추정 및 공간예측 부호화를 효율적으로 생략하여 부호화 모드 결정을 빠르게 수행하는 고속 모드 결정법을 제안한다. 실험결과, 제안된 방법은 부호화 효율의 손실이 거의 없으면서도 계산법을 약 4배 향상시킨다.

뇌졸중 환자의 위팔 손상 수준에 따른 위팔 활동과 일상생활 활동의 예측도 분석 - 임상적 평가를 이용한 예비 연구 - (Predictive Analyses for Activities of the Upper Extremity and Daily Living based on Impairment of the Upper Extremity in People with Stroke - Preliminary Study using Clinical Scales -)

  • 정영일;우영근
    • PNF and Movement
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    • 제16권3호
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    • pp.495-503
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    • 2018
  • Purpose: This study analyzes the predictive power of upper extremity activity and the activities of daily living in patients with stroke using an easy-to-use evaluation tool. Methods: The Fugl-Meyer assessment (FMA) of the upper extremity and action research arm test (ARAT) are performed, and the Korean modified Barthel index (K-MBI) is measured. The predictive power of the upper extremity activity level and the daily activity level are analyzed using regression analysis. The statistical significance level is 0.05. Results: The coefficient of determination, R2, for predicting the ARAT using FMA was high at 0.88, but the regression equation for predicting the K-MBI using the FMA and ARAT did not show a statistically significant difference. Conclusion: The assessment of the upper extremity should be performed at the activity level, as well as the impairment level. The assessment for predicting the activities of daily living should be carried out for each level of the international classification of functioning (ICF), disability, and health, which can be linked to daily life, in addition to the assessment of the upper arm. Future research should conduct more diverse analyses using the ICF assessment tools at various levels.

Determinants of Functional MicroRNA Targeting

  • Hyeonseo Hwang;Hee Ryung Chang;Daehyun Baek
    • Molecules and Cells
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    • 제46권1호
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    • pp.21-32
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    • 2023
  • MicroRNAs (miRNAs) play cardinal roles in regulating biological pathways and processes, resulting in significant physiological effects. To understand the complex regulatory network of miRNAs, previous studies have utilized massivescale datasets of miRNA targeting and attempted to computationally predict the functional targets of miRNAs. Many miRNA target prediction tools have been developed and are widely used by scientists from various fields of biology and medicine. Most of these tools consider seed pairing between miRNAs and their mRNA targets and additionally consider other determinants to improve prediction accuracy. However, these tools exhibit limited prediction accuracy and high false positive rates. The utilization of additional determinants, such as RNA modifications and RNA-binding protein binding sites, may further improve miRNA target prediction. In this review, we discuss the determinants of functional miRNA targeting that are currently used in miRNA target prediction and the potentially predictive but unappreciated determinants that may improve prediction accuracy.

터보기계에 적용되는 유체 윤활 베어링 및 댐퍼의 최신 연구 동향 (Recent Advances in Fluid Film Bearings and Dampers for Turbomachinery)

  • 이호원;정현성;김규만;이찬우;임호민;신세기;최승호;류근
    • Tribology and Lubricants
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    • 제36권4호
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    • pp.215-231
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    • 2020
  • The paper presents extensive survey and review of experimental and analytical researches on fluid film bearings and squeeze film dampers (SFDs) for turbomachinery available in open literature (major archival international journals) published recently (2018 and 2019 only). Over 60 published research works are reviewed based on the research topics and objectives, the types of bearings, size of bearings, and main design parameters with a brief summary of experiments and/or predictions in each work. Some important findings and general observations about the experimental and/or predictive data are also presented. There are several major trends observed throughout the survey. A large portion of the papers focuses on bearing surface textures and effect of operating and assembly conditions on static and/or dynamic forced performances, as well as bearing surface roughness and wear patterns. Researches on geometry of orifices and recesses in hydrostatic (or hybrid) bearings, as well as bearing system stability predictions using thermohydrodynamic analysis and computational fluid dynamics (CFD), are considered as significant topics. Studies on SFDs mainly focus on experimental identification of force coefficients for various SFD geometries and sealing conditions. Reliable experiments of fluid film bearings and SFDs along with the development of experimentally benchmarked predictive tools enable reinforcement of the path for reliable implementations of the bearing components into high performance rotating machinery operating at extreme and harsh conditions. The extensive list of sources of recent experiments in the available open literature is a welcome addition to the analytical community to gauge the accuracy of predictive tools.