• Title/Summary/Keyword: baseline reliability function

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Estimating the Mixture of Proportional Hazards Model with the Constant Baseline Hazards Function

  • Kim Jong-woon;Eo Seong-phil
    • Proceedings of the Korean Reliability Society Conference
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    • 2005.06a
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    • pp.265-269
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    • 2005
  • Cox's proportional hazards model (PHM) has been widely applied in the analysis of lifetime data, and it can be characterized by the baseline hazard function and covariates influencing systems' lifetime, where the covariates describe operating environments (e.g. temperature, pressure, humidity). In this article, we consider the constant baseline hazard function and a discrete random variable of a covariate. The estimation procedure is developed in a parametric framework when there are not only complete data but also incomplete one. The Expectation-Maximization (EM) algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

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ON THE CLASS OF TRANSMUTED-G DISTRIBUTIONS

  • AHMAD, MORAD;AL-AQTASH, RAID;AKINSETE, ALFRED
    • Journal of applied mathematics & informatics
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    • v.40 no.5_6
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    • pp.925-931
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    • 2022
  • In this article, we compare the reliability and the hazard function between a baseline distribution and the corresponding transmuted-G distribution. Some examples based on existing transmuted-G distributions in literature are used. Three tests of parameter significance are utilized to test the importance of a transmuted-G distribution over the baseline distribution, and real data is used in an application of the inference about the importance of transmuted-G distributions.

Application of the Robust and Reliability-Based Design Optimization to the Aircraft Wing Design (항공기 날개 설계를 위한 강건성 및 신뢰성 최적 설계 기법의 적용)

  • 전상욱;이동호;전용희;김정화
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.34 no.8
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    • pp.24-32
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    • 2006
  • Using a deterministic design optimization, the effect of uncertainty can result in violation of constraints and deterioration of performances. For this reason, design optimization is required to guarantee reliability for constraints and ensure robustness for an objective function under uncertainty. Therefore, this study drew Monte Carlo Simulation(MCS) for the evaluation of reliability and robustness, and selected an artificial neural network as an approximate model that is suitable for MCS. Applying to the aero-structural optimization problem of aircraft wing, we can explore robuster optima satisfying the sigma level of reliability than the baseline.

Introduction to the Validation Module Design for CMDPS Baseline Products

  • Kim, Shin-Young;Chung, Chu-Yong;Ou, Mi-Lim
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.146-148
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    • 2007
  • CMDPS (COMS Meteorological Data Processing System) is the operational meteorological products extraction system for data observed from COMS (Communication, Ocean and Meteorological Satellite) meteorological imager. CMDPS baseline products consist of 16 parameters including cloud information, water vapor products, surface information, environmental products and atmospheric motion vector. Additionally, CMDPS includes the function of calibration monitoring, and validation mechanism of the baseline products. The main objective of CMDPS validation module development is near-real time monitoring for the accuracy and reliability of the whole CMDPS products. Also, its long time validation statistics are used for upgrade of CMDPS such as algorithm parameter tuning and retrieval algorithm modification. This paper introduces the preliminary design on CMDPS validation module.

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Availability of a Maintained System

  • Jung, Hai-Sung
    • International Journal of Reliability and Applications
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    • v.3 no.4
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    • pp.185-198
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    • 2002
  • In the traditional life testing model, it is assumed that a certain number of identical items are tested under identical condition. This is due to statistical rather than practical considerations. The proportional hazards model can be used to develop a realistic approach to determine the performance of an item. That is also capable of modeling the failure rates of accelerated life testing when the covariates are applied stresses. The proportional hazards model is typically applied for a group of items to assess the importance of factors that may influence the reliability of an item. In this paper we considered the interarrival times of an item rather than the time to first failure for grouped items and provided the availability estimation for the determination of maintenance policy and overhaul time. In order to demonstrate the proposed approach, an example is presented.

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Analyzing Survival Data by Proportional Reversed Hazard Model

  • Gupta, Ramesh C.;Wu, Han
    • International Journal of Reliability and Applications
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    • v.2 no.1
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    • pp.1-26
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    • 2001
  • The purpose of this paper is to introduce a proportional reversed hazard rate model, in contrast to the celebrated proportional hazard model, and study some of its structural properties. Some criteria of ageing are presented and the inheritance of the ageing notions (of the base line distribution) by the proposed model are studied. Two important data sets are analyzed: one uncensored and the other having some censored observations. In both cases, the confidence bands for the failure rate and survival function are investigated. In one case the failure rate is bathtub shaped and in the other it is upside bath tub shaped and thus the failure rates are non-monotonic even though the baseline failure rate is monotonic. In addition, the estimates of the turning points of the failure rates are provided.

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Classification of Three Different Emotion by Physiological Parameters

  • Jang, Eun-Hye;Park, Byoung-Jun;Kim, Sang-Hyeob;Sohn, Jin-Hun
    • Journal of the Ergonomics Society of Korea
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    • v.31 no.2
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    • pp.271-279
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    • 2012
  • Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

Aircraft derivative design optimization considering global sensitivity and uncertainty of analysis models

  • Park, Hyeong-Uk;Chung, Joon;Lee, Jae-Woo
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.2
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    • pp.268-283
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    • 2016
  • Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

Effectiveness of Mental Practice on EMG Activity of the Quadriceps during Sit-to-Stand and Stand-to-Sit Tasks in a Hemiplegic Patient (상상연습이 일어서기와 앉기 과제를 수행하는 동안 편마비 환자의 대퇴사두근 활성도에 미치는 영향)

  • Kim, Jin-Seop;Kim, Suhn-Yeop;Oh, Duck-Won
    • Journal of Korean Physical Therapy Science
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    • v.15 no.3
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    • pp.43-54
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    • 2008
  • Background : We aimed to determine the effect of a mental practice on the electromyography (EMG) activity of the quadriceps femoris muscle of the affected side in a hemiplegic patient during sit-to-stand and stand-to-sit tasks. Methods : We recruited a male patient who had suffered from right hemiplegia. A single-subject experimental A-B-A design was used. The reliability of visual analysis, which was primarily employed in this study design, was supported by using the "2- standard-deviation band" method. The target motions consisted of two activities: sit-to-stand and stand-to-sit. The EMG measurements of the quadriceps femoris muscles of the affected and unaffected sides were made in 8 sessions in the baseline (A), mental-practice (B), and follow-up (A) phases. During the mental practice phase, the 10-min mental practice was performed, and the mental practice was withdrawn in the follow-up phase in order to identify the carry-over effects of the treatment. Data was calculated as the percentage of the ratio of the quadriceps EMG activity values of the affected side on unaffected side. Result : The percentage EMG-activity ratio showed a greater increase in the mental-practice phase than in the baseline, and it was maintained during the follow-up phase. Most of the data points in the mental-practice and follow-up phases were positioned above the "2-standard-deviation band." Conclusion : These findings suggest that mental practice can be used to improve the physical function of hemiplegic patients.

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Robust Speech Recognition Using Missing Data Theory (손실 데이터 이론을 이용한 강인한 음성 인식)

  • 김락용;조훈영;오영환
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.3
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    • pp.56-62
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    • 2001
  • In this paper, we adopt a missing data theory to speech recognition. It can be used in order to maintain high performance of speech recognizer when the missing data occurs. In general, hidden Markov model (HMM) is used as a stochastic classifier for speech recognition task. Acoustic events are represented by continuous probability density function in continuous density HMM(CDHMM). The missing data theory has an advantage that can be easily applicable to this CDHMM. A marginalization method is used for processing missing data because it has small complexity and is easy to apply to automatic speech recognition (ASR). Also, a spectral subtraction is used for detecting missing data. If the difference between the energy of speech and that of background noise is below given threshold value, we determine that missing has occurred. We propose a new method that examines the reliability of detected missing data using voicing probability. The voicing probability is used to find voiced frames. It is used to process the missing data in voiced region that has more redundant information than consonants. The experimental results showed that our method improves performance than baseline system that uses spectral subtraction method only. In 452 words isolated word recognition experiment, the proposed method using the voicing probability reduced the average word error rate by 12% in a typical noise situation.

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