In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken a...In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.展开更多
Estimation of random errors, which are due to shot noise of photomultiplier tube(PMT) or avalanche photodiode(APD) detectors, is very necessary in lidar observation. Due to the Poisson distribution of incident electro...Estimation of random errors, which are due to shot noise of photomultiplier tube(PMT) or avalanche photodiode(APD) detectors, is very necessary in lidar observation. Due to the Poisson distribution of incident electrons, there still exists a proportional relationship between standard deviation and square root of its mean value. Based on this relationship,noise scale factor(NSF) is introduced into the estimation, which only needs a single data sample. This method overcomes the distractions of atmospheric fluctuations during calculation of random errors. The results show that this method is feasible and reliable.展开更多
A block representation of the BLU factorization for block tridiagonal matrices is presented. Some properties on the factors obtained in the course of the factorization are studied. Simpler expressions for errors incur...A block representation of the BLU factorization for block tridiagonal matrices is presented. Some properties on the factors obtained in the course of the factorization are studied. Simpler expressions for errors incurred at the process of the factorization for block tridiagonal matrices are considered.展开更多
The majority of errors in healthcare are from systems factors that create the latent conditions for error to occur. The majority of occupational stressors causing burnout are also the result of systemic factors. Advan...The majority of errors in healthcare are from systems factors that create the latent conditions for error to occur. The majority of occupational stressors causing burnout are also the result of systemic factors. Advances in technology create new levels of stress and expectations on healthcare workers (HCW) with an endless infusion of requirements from multiple authoritative sources that are tracked and monitored. The quality of care and safety of patients is affected by the wellbeing of HCWs who now practice in an environment that has become more complex to navigate, often expending limited neural resource (brainpower) on classifying, organizing, constantly making decisions on how and when they can accomplish what is required(extraneous cognitive load) in addition to direct patient care. New information demonstrates profound biological impact on the brains of those who have burnout in areas that affect the quality and safety of the decisions they make-which affects risk to patients in healthcare. Healthcare administration curriculum currently does not include ways to address these stress-induced problems in healthcare delivery. The science of human factors and ergonomics (HFE) promotes system performance and worker wellbeing. Patient safety is one component of system performance. Since many requirements come without resource to accomplish them, it becomes incumbent upon health system leadership to organize the means for completion of these to minimize the needless loss of brain power diverted away from the delivery of patient care. Human Factor-Based Leadership (HFBL) is an interactive, problem solving seminar series designed for healthcare leaders. The purpose is to provide relevant human factor science to integrate into their leadership and management decisions to make HCWs occupational environment more manageable and sustainable-which makes safer conditions for clinician wellbeing and patient care. After learning the content, a cohort of healthcare leaders believed that adequately addressing HFE in healthcare delivery would significantly reduce clinician burnout and risk of latent errors from upstream leadership decisions. An overview of the content of the seminars is described. Leadership feedback on usability of these seminars is reported. Three HFBL seminars described are Human Factor Relevance in Leadership, Biopsychosocial Approach to Wellness and Burnout, Human Factor Based Leadership: Examples and Applications.展开更多
增益噪声温度比(Gain to Noise Temperature Ratio,G/T)是衡量卫星地面接收系统性能的关键指标,其测量精度直接影响系统性能评估的有效性。为提高G/T值的测量精度,系统阐述了利用射电源进行G/T值测试的原理和方法,提出了射电源大气吸收...增益噪声温度比(Gain to Noise Temperature Ratio,G/T)是衡量卫星地面接收系统性能的关键指标,其测量精度直接影响系统性能评估的有效性。为提高G/T值的测量精度,系统阐述了利用射电源进行G/T值测试的原理和方法,提出了射电源大气吸收修正因子、波束展宽修正因子、射电源流量随时间变化修正因子的精确计算模型,并给出了射电源通量密度曲线及修正因子曲线。在此基础上,利用月亮和仙后座A对中等口径天线进行G/T值测量,系统分析了G/T值的测量误差,验证了所提计算模型的有效性,为提高G/T值测量的精确性与可靠性提供了科学依据和实践指导。展开更多
Monte Carlo method was adopted to calculate the meshing error considering the manufacture error and assembly error of the meshing point along the time-varying contact line for helical gear pair. The flexural-torsion-a...Monte Carlo method was adopted to calculate the meshing error considering the manufacture error and assembly error of the meshing point along the time-varying contact line for helical gear pair. The flexural-torsion-axis dynamic model coupled was established under the tooth friction force and solved by the perturbation method to compute real dynamic tooth load. The change laws of the friction force and friction torque were obtained in a meshing period. The transmission error formulation was analyzed to introduce meshing excitations. The maximum dynamic transmission error, the maximum meshing force and the maximum dynamic factor were calculated under different speeds, external loads and damping factors. The conclusions can provide theoretical basis for the gear design especially in tooth profile correction.展开更多
Software defect prevention is an important way to reduce the defect introduction rate.As the primary cause of software defects,human error can be the key to understanding and preventing software defects.This paper pro...Software defect prevention is an important way to reduce the defect introduction rate.As the primary cause of software defects,human error can be the key to understanding and preventing software defects.This paper proposes a defect prevention approach based on human error mechanisms：DPe HE.The approach includes both knowledge and regulation training in human error prevention.Knowledge training provides programmers with explicit knowledge on why programmers commit errors,what kinds of errors tend to be committed under different circumstances,and how these errors can be prevented.Regulation training further helps programmers to promote the awareness and ability to prevent human errors through practice.The practice is facilitated by a problem solving checklist and a root cause identification checklist.This paper provides a systematic framework that integrates knowledge across disciplines,e.g.,cognitive science,software psychology and software engineering to defend against human errors in software development.Furthermore,we applied this approach in an international company at CMM Level 5 and a software development institution at CMM Level 1 in the Chinese Aviation Industry.The application cases show that the approach is feasible and effective in promoting developers＇ ability to prevent software defects,independent of process maturity levels.展开更多
Aiming at the Four-Dimensional Variation source term inversion algorithm proposed earlier,the observation error regularization factor is introduced to improve the prediction accuracy of the diffusion model,and an impr...Aiming at the Four-Dimensional Variation source term inversion algorithm proposed earlier,the observation error regularization factor is introduced to improve the prediction accuracy of the diffusion model,and an improved Four-Dimensional Variation source term inversion algorithm with observation error regularization(OER-4DVAR STI model)is formed.Firstly,by constructing the inversion process and basic model of OER-4DVAR STI model,its basic principle and logical structure are studied.Secondly,the observation error regularization factor estimation method based on Bayesian optimization is proposed,and the error factor is separated and optimized by two parameters:error statistical time and deviation degree.Finally,the scientific,feasible and advanced nature of the OER-4DVAR STI model are verified by numerical simulation and tracer test data.The experimental results show that OER-4DVAR STI model can better reverse calculate the hazard source term information under the conditions of high atmospheric stability and flat underlying surface.Compared with the previous inversion algorithm,the source intensity estimation accuracy of OER-4DVAR STI model is improved by about 46.97%,and the source location estimation accuracy is improved by about 26.72%.展开更多
To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to e...To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.展开更多
Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predict...Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predictive control algorithm(SPC). The new method uses model matching error to calculate the variable forgetting factor, and applies it to constructing Hankel data matrix.This makes the data represent the changes of system information better. For eliminating the steady state error, the derivation of the incremental control is made. Simulation results on a rotary kiln show that this control strategy has achieved a good control effect.展开更多
Many medication errors could be avoided if administration was more closely linked with structured monitoring. The contributory factors to administration errors occurred in one recent year were reviewed and identified ...Many medication errors could be avoided if administration was more closely linked with structured monitoring. The contributory factors to administration errors occurred in one recent year were reviewed and identified contributory factors to errors as six domains of administration principles according to the report from the Quality and Safety website. The current measures including guidelines, policy, and practices to prevent the administration errors identified in the previous step were searched from the United Christian Hospital (UCH) homepage. Meanwhile, the international measures suggested in literature were identified to address the administration errors identified. 41 cases were identified as medication errors related to administration error events, with total twenty contributory factors identified according to the incident report which identified five contributory factors as common causes. Measures to prevent interruption of medication round and measures to improve individual knowledge and skills, and personal responsebility were suggested to fill the gaps. The medication administration errors should be avoided through both education reinforcing programme and preventive interventions of distraction or interruption to the procedure after comparing the existing measures to the suggested measures from literature. This study was so important to improve the current measures to prevent medication administration errors.展开更多
The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of t...The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of the dynamic mathematical model is researched. By means of theoretical analysis, the error formulas, the error sign criteria and the error relationship criterion of the implicit Euler method and the trapezoidal method are given, the dynamic factor affecting the computational accuracy has been found, the formula and the methods of computing the dynamic factor are given. The computational accuracy of the dynamic mathematical model like this can be improved by use of the dynamic factor.展开更多
This paper discusses some of the key aspects of human factors in anaesthesia for the improvement of patient safety. Medical errors have emerged as a serious issue in healthcare delivery. There has been new interest in...This paper discusses some of the key aspects of human factors in anaesthesia for the improvement of patient safety. Medical errors have emerged as a serious issue in healthcare delivery. There has been new interest in human factors as a means of reducing these errors. Human factors are important contributors to critical incidents and crises in anaesthesia. It has been shown that the prevalence of human factors in anaesthesia can be as high as 83%. Cognitive thinking process and biases involved are important in understanding human factors. Errors of cognition linked with human factors lead to anaesthetic errors and crisis. Multiple errors in the cognitive thinking process, known as "Cognitive dispositions to respond" have been identified leading to errors. These errors classified into latent or active can be easily identified in the clinical vignettes of serious medical errors. Application of the knowledge on human factors and use of cognitive de-biasing strategies can avoid human errors. These strategies could involve use of checklists, strategies to cope with stress and fatigue and the use of standard operating procedures. A safety culture and health care model designed to promote patient safety can compliment this further. Incorporation of these strategies strengthens the defence layers against the "Swiss Cheese" models, which exist in the health care industry.展开更多
This paper presents a new method for soft error detection using software redundancy (SEDSR) that is able to detect transient faults. Soft errors damage the control flow and data of programs and designers usually use h...This paper presents a new method for soft error detection using software redundancy (SEDSR) that is able to detect transient faults. Soft errors damage the control flow and data of programs and designers usually use hardware-based solutions to handle them. Software-based techniques for soft error detection force less cost and delay to systems and do not change their configuration. Therefore, these kinds of methods are appropriate alternatives for hardware-based techniques. SEDSR has two separate parts for data and control flow errors detection. Fault injection method is used to compare SEDSR with previous methods of this field based on the new parameter of “Evaluation Factor” that takes in account fault coverage, memory and performance overheads. These parameters are important in real time safety critical applications. Experimental results on SPEC2000 and some traditional benchmarks of this field show that SEDSR is much better than previous methods of this field. SEDSR’s evaluation factor is about 50% better than other methods of this field. These results show its success in satisfaction of the existing tradeoff between fault coverage, performance and memory overheads.展开更多
基金This work is funded by the National Natural Science Foundation of China(Grant Nos.42377164 and 52079062)the National Science Fund for Distinguished Young Scholars of China(Grant No.52222905).
文摘In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB05040300)the National Natural Science Foundation of China(Grant No.41205119)
文摘Estimation of random errors, which are due to shot noise of photomultiplier tube(PMT) or avalanche photodiode(APD) detectors, is very necessary in lidar observation. Due to the Poisson distribution of incident electrons, there still exists a proportional relationship between standard deviation and square root of its mean value. Based on this relationship,noise scale factor(NSF) is introduced into the estimation, which only needs a single data sample. This method overcomes the distractions of atmospheric fluctuations during calculation of random errors. The results show that this method is feasible and reliable.
文摘A block representation of the BLU factorization for block tridiagonal matrices is presented. Some properties on the factors obtained in the course of the factorization are studied. Simpler expressions for errors incurred at the process of the factorization for block tridiagonal matrices are considered.
文摘The majority of errors in healthcare are from systems factors that create the latent conditions for error to occur. The majority of occupational stressors causing burnout are also the result of systemic factors. Advances in technology create new levels of stress and expectations on healthcare workers (HCW) with an endless infusion of requirements from multiple authoritative sources that are tracked and monitored. The quality of care and safety of patients is affected by the wellbeing of HCWs who now practice in an environment that has become more complex to navigate, often expending limited neural resource (brainpower) on classifying, organizing, constantly making decisions on how and when they can accomplish what is required(extraneous cognitive load) in addition to direct patient care. New information demonstrates profound biological impact on the brains of those who have burnout in areas that affect the quality and safety of the decisions they make-which affects risk to patients in healthcare. Healthcare administration curriculum currently does not include ways to address these stress-induced problems in healthcare delivery. The science of human factors and ergonomics (HFE) promotes system performance and worker wellbeing. Patient safety is one component of system performance. Since many requirements come without resource to accomplish them, it becomes incumbent upon health system leadership to organize the means for completion of these to minimize the needless loss of brain power diverted away from the delivery of patient care. Human Factor-Based Leadership (HFBL) is an interactive, problem solving seminar series designed for healthcare leaders. The purpose is to provide relevant human factor science to integrate into their leadership and management decisions to make HCWs occupational environment more manageable and sustainable-which makes safer conditions for clinician wellbeing and patient care. After learning the content, a cohort of healthcare leaders believed that adequately addressing HFE in healthcare delivery would significantly reduce clinician burnout and risk of latent errors from upstream leadership decisions. An overview of the content of the seminars is described. Leadership feedback on usability of these seminars is reported. Three HFBL seminars described are Human Factor Relevance in Leadership, Biopsychosocial Approach to Wellness and Burnout, Human Factor Based Leadership: Examples and Applications.
文摘增益噪声温度比(Gain to Noise Temperature Ratio,G/T)是衡量卫星地面接收系统性能的关键指标,其测量精度直接影响系统性能评估的有效性。为提高G/T值的测量精度,系统阐述了利用射电源进行G/T值测试的原理和方法,提出了射电源大气吸收修正因子、波束展宽修正因子、射电源流量随时间变化修正因子的精确计算模型,并给出了射电源通量密度曲线及修正因子曲线。在此基础上,利用月亮和仙后座A对中等口径天线进行G/T值测量,系统分析了G/T值的测量误差,验证了所提计算模型的有效性,为提高G/T值测量的精确性与可靠性提供了科学依据和实践指导。
基金Supported by National Basic Research Program of China("973"Program,No.2013CB632305)
文摘Monte Carlo method was adopted to calculate the meshing error considering the manufacture error and assembly error of the meshing point along the time-varying contact line for helical gear pair. The flexural-torsion-axis dynamic model coupled was established under the tooth friction force and solved by the perturbation method to compute real dynamic tooth load. The change laws of the friction force and friction torque were obtained in a meshing period. The transmission error formulation was analyzed to introduce meshing excitations. The maximum dynamic transmission error, the maximum meshing force and the maximum dynamic factor were calculated under different speeds, external loads and damping factors. The conclusions can provide theoretical basis for the gear design especially in tooth profile correction.
文摘Software defect prevention is an important way to reduce the defect introduction rate.As the primary cause of software defects,human error can be the key to understanding and preventing software defects.This paper proposes a defect prevention approach based on human error mechanisms：DPe HE.The approach includes both knowledge and regulation training in human error prevention.Knowledge training provides programmers with explicit knowledge on why programmers commit errors,what kinds of errors tend to be committed under different circumstances,and how these errors can be prevented.Regulation training further helps programmers to promote the awareness and ability to prevent human errors through practice.The practice is facilitated by a problem solving checklist and a root cause identification checklist.This paper provides a systematic framework that integrates knowledge across disciplines,e.g.,cognitive science,software psychology and software engineering to defend against human errors in software development.Furthermore,we applied this approach in an international company at CMM Level 5 and a software development institution at CMM Level 1 in the Chinese Aviation Industry.The application cases show that the approach is feasible and effective in promoting developers＇ ability to prevent software defects,independent of process maturity levels.
基金Ministry of Science and Technology of the People’s Republic of China for its support and guidance(Grant No.2018YFC0214100)。
文摘Aiming at the Four-Dimensional Variation source term inversion algorithm proposed earlier,the observation error regularization factor is introduced to improve the prediction accuracy of the diffusion model,and an improved Four-Dimensional Variation source term inversion algorithm with observation error regularization(OER-4DVAR STI model)is formed.Firstly,by constructing the inversion process and basic model of OER-4DVAR STI model,its basic principle and logical structure are studied.Secondly,the observation error regularization factor estimation method based on Bayesian optimization is proposed,and the error factor is separated and optimized by two parameters:error statistical time and deviation degree.Finally,the scientific,feasible and advanced nature of the OER-4DVAR STI model are verified by numerical simulation and tracer test data.The experimental results show that OER-4DVAR STI model can better reverse calculate the hazard source term information under the conditions of high atmospheric stability and flat underlying surface.Compared with the previous inversion algorithm,the source intensity estimation accuracy of OER-4DVAR STI model is improved by about 46.97%,and the source location estimation accuracy is improved by about 26.72%.
基金Supported by the National Thousand Talents Program of Chinathe National Natural Science Foundation of China(61473054)the Fundamental Research Funds for the Central Universities of China
文摘To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.
文摘Aiming at the time-varying characteristics of industrial process, this paper introduces an adaptive subspace predictive control(ASPC) strategy with time-varying forgetting factor based on the original subspace predictive control algorithm(SPC). The new method uses model matching error to calculate the variable forgetting factor, and applies it to constructing Hankel data matrix.This makes the data represent the changes of system information better. For eliminating the steady state error, the derivation of the incremental control is made. Simulation results on a rotary kiln show that this control strategy has achieved a good control effect.
文摘Many medication errors could be avoided if administration was more closely linked with structured monitoring. The contributory factors to administration errors occurred in one recent year were reviewed and identified contributory factors to errors as six domains of administration principles according to the report from the Quality and Safety website. The current measures including guidelines, policy, and practices to prevent the administration errors identified in the previous step were searched from the United Christian Hospital (UCH) homepage. Meanwhile, the international measures suggested in literature were identified to address the administration errors identified. 41 cases were identified as medication errors related to administration error events, with total twenty contributory factors identified according to the incident report which identified five contributory factors as common causes. Measures to prevent interruption of medication round and measures to improve individual knowledge and skills, and personal responsebility were suggested to fill the gaps. The medication administration errors should be avoided through both education reinforcing programme and preventive interventions of distraction or interruption to the procedure after comparing the existing measures to the suggested measures from literature. This study was so important to improve the current measures to prevent medication administration errors.
文摘The computational methods of a typical dynamic mathematical model that can describe the differential element and the inertial element for the system simulation are researched. The stability of numerical solutions of the dynamic mathematical model is researched. By means of theoretical analysis, the error formulas, the error sign criteria and the error relationship criterion of the implicit Euler method and the trapezoidal method are given, the dynamic factor affecting the computational accuracy has been found, the formula and the methods of computing the dynamic factor are given. The computational accuracy of the dynamic mathematical model like this can be improved by use of the dynamic factor.
文摘This paper discusses some of the key aspects of human factors in anaesthesia for the improvement of patient safety. Medical errors have emerged as a serious issue in healthcare delivery. There has been new interest in human factors as a means of reducing these errors. Human factors are important contributors to critical incidents and crises in anaesthesia. It has been shown that the prevalence of human factors in anaesthesia can be as high as 83%. Cognitive thinking process and biases involved are important in understanding human factors. Errors of cognition linked with human factors lead to anaesthetic errors and crisis. Multiple errors in the cognitive thinking process, known as "Cognitive dispositions to respond" have been identified leading to errors. These errors classified into latent or active can be easily identified in the clinical vignettes of serious medical errors. Application of the knowledge on human factors and use of cognitive de-biasing strategies can avoid human errors. These strategies could involve use of checklists, strategies to cope with stress and fatigue and the use of standard operating procedures. A safety culture and health care model designed to promote patient safety can compliment this further. Incorporation of these strategies strengthens the defence layers against the "Swiss Cheese" models, which exist in the health care industry.
文摘This paper presents a new method for soft error detection using software redundancy (SEDSR) that is able to detect transient faults. Soft errors damage the control flow and data of programs and designers usually use hardware-based solutions to handle them. Software-based techniques for soft error detection force less cost and delay to systems and do not change their configuration. Therefore, these kinds of methods are appropriate alternatives for hardware-based techniques. SEDSR has two separate parts for data and control flow errors detection. Fault injection method is used to compare SEDSR with previous methods of this field based on the new parameter of “Evaluation Factor” that takes in account fault coverage, memory and performance overheads. These parameters are important in real time safety critical applications. Experimental results on SPEC2000 and some traditional benchmarks of this field show that SEDSR is much better than previous methods of this field. SEDSR’s evaluation factor is about 50% better than other methods of this field. These results show its success in satisfaction of the existing tradeoff between fault coverage, performance and memory overheads.
