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This article sets itself against the bulk of scholarship on surveillance, which is characterized by emphasis either on Michel Foucault’s analysis of the Panopticon, or on Gilles Deleuze’s too-brief “Postscript on the Societies of Control.” In contrast to these dominant critical paradigms, the article recuperates a mode of governmentality proposed in Foucault’s last lectures on “Security,” in order to draw out the latent instabilities that beset contemporary surveillance systems and hence reveal the possibility of resisting them. The article’s recuperation of “Security” proceeds by way of close readings of workplace documentaries by radical filmmakers Harun Farocki (Die Schöpfer der Einkaufswelten, Ein neues Produkt, and other films) and Carmen Losmann (Work Hard Play Hard). When analyzed in concert with Foucault’s neglected late lectures, and in a final move with the post-Freudian theory of perversion, these films prompt new reflection on complicity with surveillance and, importantly, the unexpected potential of that complicity as an error in the systems of contemporary workplaces and leisure-spaces.

This paper reviews the development of the ensemble Kalman filter (EnKF) for atmospheric data assimilation. Particular attention is devoted to recent advances and current challenges. The distinguishing properties of three well-established variations of the EnKF algorithm are first discussed. Given the limited size of the ensemble and the unavoidable existence of errors whose origin is unknown (i.e., system error), various approaches to localizing the impact of observations and to accounting for these errors have been proposed. However, challenges remain; for example, with regard to localization of multiscale phenomena (both in time and space). For the EnKF in general, but higher-resolution applications in particular, it is desirable to use a short assimilation window. This motivates a focus on approaches for maintaining balance during the EnKF update. Also discussed are limited-area EnKF systems, in particular with regard to the assimilation of radar data and applications to tracking severe storms and tropical cyclones. It seems that relatively less attention has been paid to optimizing EnKF assimilation of satellite radiance observations, the growing volume of which has been instrumental in improving global weather predictions. There is also a tendency at various centers to investigate and implement hybrid systems that take advantage of both the ensemble and the variational data assimilation approaches; this poses additional challenges and it is not clear how it will evolve. It is concluded that, despite more than 10 years of operational experience, there are still many unresolved issues that could benefit from further research. Contents Introduction...4490 Popular flavors of the EnKF algorithm...4491 General description...4491 Stochastic and deterministic filters...4492 The stochastic filter...4492 The deterministic filter...4492 Sequential or local filters...4493 Sequential ensemble Kalman filters...4493 The local ensemble transform Kalman filter...4494 Extended state vector...4494 Issues for the development of algorithms...4495 Use of small ensembles...4495 Monte Carlo methods...4495 Validation of reliability...4497 Use of group filters with no inbreeding...4498 Sampling error due to limited ensemble size: The rank problem...4498 Covariance localization...4499 Localization in the sequential filter...4499 Localization in the LETKF...4499 Issues with localization...4500 Summary...4501 Methods to increase ensemble spread...4501 Covariance inflation...4501 Additive inflation...4501 Multiplicative inflation...4502 Relaxation to prior ensemble information...4502 Issues with inflation...4503 Diffusion and truncation...4503 Error in physical parameterizations...4504 Physical tendency perturbations...4504 Multimodel, multiphysics, and multiparameter approaches...4505 Future directions...4505 Realism of error sources...4506 Balance and length of the assimilation window...4506 The need for balancing methods...4506 Time-filtering methods...4506 Toward shorter assimilation windows...4507 Reduction of sources of imbalance...4507 Regional data assimilation...4508 Boundary conditions and consistency across multiple domains...4509 Initialization of the starting ensemble...4510 Preprocessing steps for radar observations...4510 Use of radar observations for convective-scale analyses...4511 Use of radar observations for tropical cyclone analyses...4511 Other issues with respect to LAM data assimilation...4511 The assimilation of satellite observations...4512 Covariance localization...4512 Data density...4513 Bias-correction procedures...4513 Impact of covariance cycling...4514 Assumptions regarding observational error...4514 Recommendations regarding satellite observations...4515 Computational aspects...4515 Parameters with an impact on quality...4515 Overview of current parallel algorithms...4516 Evolution of computer architecture...4516 Practical issues...4517 Approaching the gray zone...4518 Summary...4518 Hybrids with variational and EnKF components...4519 Hybrid background error covariances...4519 E4DVar with the α control variable...4519 Not using linearized models with 4DEnVar...4520 The hybrid gain algorithm...4521 Open issues and recommendations...4521 Summary and discussion...4521 Stochastic or deterministic filters...4522 The nature of system error...4522 Going beyond the synoptic scales...4522 Satellite observations...4523 Hybrid systems...4523 Future of the EnKF...4523 APPENDIX A...4524 Types of Filter Divergence...4524 Classical filter divergence...4524 Catastrophic filter divergence...4524 APPENDIX B...4524 Systems Available for Download...4524 References...4525

Highlights • Identity fraud is becoming a more recognizable challenge, particularly with the introduction of electronic medical records. • Particularly in surgery, identity fraud can result in significant harm to patients and burden to the health care system. • Clinical vigilance and implementation of strategies to reduce system error can reduce the negative impact of identity fraud., Introduction This case series highlights the challenges faced in general surgery when encountering patients who use multiple false identities and provide unreliable histories. Presentation of cases We present two patients both with a background of mental health disorders and previous abdominal surgeries. After extensive workup with one patient almost proceeding to surgery, it was noted that these patients have had multiple presentations under different aliases to multiple different hospitals and had given inconsistent medical and surgical histories. Discussion In such patients, history and clinical examinations are unreliable. Medical records are also not helpful given the patients’ multiple aliases. Particularly in surgery, inaccurate knowledge of the patients’ previous operative details can lead to significant harms. Extensive investigations are usually performed in assessing these patients, resulting in excessive radiation exposure and incurring significant costs to the health system. It is also important to recognise the potential legal repercussions and harms to the patients who have had their identities stolen. Conclusion Identity fraud poses significant challenges to patient care, vigilance from clinicians and implementing strategies to reduce system error can help to limit harms to the patient and the health care system.

The technique of the target information transformation processes are key technique of air defense weapon system. Inconsistent target information prone to the target data is not available, ultimately results the target not intercepted in cooperative combat air defense weapon system, In order to solve the practical engineering problems, combine theoretical basis with engineering practice, build a consistency transformation project in this paper. meanwhile, fullscale and relative sufficiency of the testing method are given. The flight test results prove that the consistency transformation project can effectively reduce the system error, and improve the target intercept probability.

In this study, a ground-based radar system with two multiple input multiple output (MIMO) arrays is developed for 2D displacement estimation applications. To reduce the influences of antenna position error, channel delay, and phase/gain difference on the imaging quality, calibration methods and phase coherence factor (PCF) based filtering methods are applied. For each MIMO array, target displacement can be measured along its line of sight direction. Co-registration is conducted to help to derive the 2D displacement vector estimations of the targets.

A comprehensive system error source analysis and calibration of an airborne along-track interferometric FMCW SAR for ocean surface currents velocity retrieval is presented. Starting with the observed phase errors from a stationary test site, three major error sources are analyzed and possible calibration approaches are derived. The range-dependent phase offsets are demonstrated to be introduced by the phase imbalance between receive channels and receive antennas of the transceiver. The phase undulations in the along-track direction are likely due to the uncompensated motion errors caused by inaccurate aircraft attitude and velocity measurements. After calibration, most of the system phase errors are removed which greatly improves the accuracy for surface velocity retrieval by ATI-SAR.

According to the definition of extinction ratio, the paper analyzed two test methods of polarizer extinction ratio, and proved that these two kinds of systematic errors caused by the approximate formula are equal under the same condition. Generally, the extinction ratio of the polarizers to be measured is 2 orders of magnitude lower than the known polarizers, and the system error can be controlled within 1%.

The causes of the system error in null mirror during interferometric testing was analyzed. The system error in null mirror were obtained by turning the tested surface in different angles along their optic axis. The corrective file was loaded into the interferometer measurement, so as to the system error can be removed directly when testing. Therefore, with this technique, the demands on the material, manufacturing, and assembly of null mirror is not so critical, and the test accuracy is improved observably.

Log data is crucial for developers, decision maker, and end-users. With log data, we can inspect whether the system error or not, give warning events or whether our system processes are loFinally, the values in this tableading successfully or not. This paper aims to provide a virtualization platform for our campus Wi-Fi log data for further analysis. Our system used ELK Stack technology. It consists of three components: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search engine which used for searching all kinds of documents, Logstash used for managing centralize, transform and stash our data to Elasticsearch, and Kibana applied for visualizing Elasticsearch data and an excellent tool for a real-time data analytics and decision making. Our data is a Netflow traffic data. Approximately our data growth up 10 MB per day and our data have grown to 19 GB until now.

The medical accidents and negligence reported frequently in the medically advanced nations of the United States, United Kingdom, and Japan are widely claimed to have been due not only to ‘human error’ but also to ‘system error’ within the medical management process in hospital organizations. Using ill-structured big-data on actual examples of medical accidents and negligence in the 17 years from 2000 to 2016, the present study analyzed more than 430 medical accidents reported in the pages of newspapers in Japan.

Summary In some recent geophysical monitoring studies, researchers have proposed a method of difference inversion, which means taking the difference between data into inversion process. It overcomes the crucial problem of the initial model for local optimization and reduce the environmental or system error in the results. Until now, there has not been an application of this method in the global inversion of Seismic Surface Waves. However using directly the difference between the dispersion curves as the data to be inverted can be not robust. Here, we propose to calculate differences between dispersion diagrams, which contains a part of the measurement uncertainty. Based on histograms distances definitions, several diagram distance calculations are used and tested numerically and experimentally in order to study the impact of the distance definition on the misfit assessment in case of a small variation about 10% in a deep part of a 2-layer medium. Results show the feasibility of this method. even if the accuracy of the the inversion result of the preliminary part remains a key issue on the assessment of medium’s variation.

In this paper, the state structure equation was studied for general systems. The static structure and dynamic structure of the system error were also studied.

The cubature Kalman filter (CKF) is an estimation method for nonlinear Gaussian systems. However, its filtering solution is affected by system error, leading to biased or diverged system state estimation. This paper proposes a randomly weighted CKF (RWCKF) to handle the CKF limitation. This method incorporates random weights in CKF to restrain system error’s influence on system state estimation by dynamic modification of cubature point weights. Randomly weighted theories are established to estimate predicted system state and system measurement as well as their covariances. Simulation and experimental results as well as comparison analyses demonstrate the presented RWCKF conquers the CKF problem, leading to enhanced accuracy for system state estimation.

The unknown system error is widespread, but it is difficult to be verified or corrected. Furthermore, it also will yield to relatively large filtering errors. As an effective solution, the incremental equation is introduced, which can eliminate these unknown system errors. Meanwhile, the accuracy of state estimators will be improved. Then, a kind of distributed fusion incremental Kalman filter is presented in this paper. It can greatly improve the accuracy of state estimation for the multisensor systems under poor observation condition. The proposed algorithm is easy to be applied in engineering practice because of its simple form and small computational burden so. The simulation results show that it is effective and feasible.

The BMA has urged NHS England to strip Capita of its contract to provide back office support services to GPs after it emerged that as many as 48 500 women have not received information about cervical cancer screening because of a system error. NHS England said that an “administrative error” had led to thousands of invitations, reminder letters, and screening results not being sent to patients. This is the latest in a series of failings12 by Capita since it was contracted to provide GP back office services under the name Primary Care Support England in September 2015. The BMA’s GP committee said that Capita’s stewardship of the service had …

Hearing loss is a common issue when people become older, resulting in problems such as depression, risk of dementia, and cognitive decline, among others. Hearing aids are computationally constrained devices that offer the possibility of solving this issue, thus improving people’s quality of life. A typical algorithm that should be implemented in these devices is Voice Activity Detection. In this work, cascade detectors are applied to reduce the computational cost while maintaining the same performance or to increase the performance while maintaining the same computational cost. This is achieved by a two-stage detector. In the first stage, a linear system determines whether the detection can be easily carried out, or a second stage with a more complex neural-network-based detection is required. This way, some of the decisions are taken without using the complex detector. The results show that the system error can be reduced up to 8.5% while using the same amount of resources. Moreover, the error is the lowest among the proposals that are affordably implemented in hearing aids.

Consecutive missing values are likely to occur in long climate data due to system error or defective equipment.Furthermore, it is difficult to impute missing values. However, these complicated problems can be overcameby imputing missing values with reference time series. Reference time series must be composed of similartime series to time series that include missing values. We performed a simulation to compare three missingimputation methods (the adjusted normal ratio method, the regression method and the IDW method) tocomplete the missing values of time series. A comparison of the three missing imputation methods for thedaily mean temperatures at 14 climatological stations indicated that the IDW method was better thanxothers at south seaside stations. We also found the regression method was better than others at moststations (except south seaside stations).Keywords: consecutive missing value, missing value imputation, adjusted normal ratio methods, regressionmethod, IDW method

Errors are a recurring fact of organizational life and can potentially yield either adverse or positive consequences. Organizational researchers and practitioners alike have become increasingly interested in understanding the causes of errors and the coping strategies that foster organizational success. Although we have learned much about errors in specific research areas across specific organizational contexts, we know little about how multifaceted forces in organizations, especially when they contradict each other, might affect the pathways of errors in organizations. This review strives to integrate the literature on errors, not only by summarizing conceptual foundations and empirical findings, but also by discussing discrepancies, inconsistencies, and opportunities for research synthesis via level of analysis, temporal dynamism, and priority lenses. At the core of this integrative review is a call for future research to explain how to reduce the underlying causes and negative consequences of errors while promoting positive outcomes and learning benefits in organizations. We close this review by offering suggestions that help develop an integrative, rather than isolated, investigation of errors in organizations.

As semiconductor technology has developed, device performance has been improved. However, since device structures became smaller, circuit aging due to operational and environmental conditions can be accelerated. Circuit aging causes a performance degradation and eventually a system error. In reliable systems, a failure due to aging might cause a great disaster. Therefore, these systems need a performance degradation prediction function so that they can take action in advance before a failure occurs. This paper presents an on-line circuit performance degradation monitoring scheme for predicting a failure by detecting performance degradation during circuit normal operation. In our proposed scheme, IEEE 1149.1 output boundary scan cells and TAP controller are reused. The experimental result shows that the proposed architecture can monitor the performance degradation during normal operation without stopping the circuit.

This paper aims to introduce a method to test vegetation classification systems based on the domi- nant species, in order to evaluate the accuracy of the classification system. If the test shows that there are er- rors in commonly used vegetation classification system, corrections are needed. To correct the existing clas- sification system error, we must build a new system of classification. This paper presents a new vegetation classification system based on dominant species, and identifies the processes and methods to establish the classification system. Logic testing tools are the basis of examining the correctness of vegetation classifica- tion system. In this paper, we confirm that the principles of logic can be used for testing classification sys- tems. Steps and methods to establish the vegetation classification systems are given and the new plant life-form and vegetation classification system are established. We suggest the concept of multi-constructive species vegetation, set, the classified status and present a clear vegetation nomenclature.

The UK’s struggling covid-19 testing system faces further disruption after a failure in the supply chain of critical test kits made by the drug company Roche. Biomedical scientists have warned that the problem, which is due to a switch to a new warehouse, could also affect testing across a whole range of conditions. This is the second glitch this week to affect England’s test and trace system, after an IT system error left 16 000 tests unreported, leading to an artificially low picture of the spread of the virus and delaying contact tracing efforts.1 Roche, one of the main suppliers of covid-19 polymerase chain reaction (PCR) and antibody tests to the NHS Test and Trace system, went live with the distribution of goods from its new national distribution centre in Sussex in September. A Roche spokesperson told The BMJ , “During the transition, we …

High precision time difference measurement between satellite and earth is an important part of space-based time-frequency system application in the future. With the on-orbit operation of high-precision atomic clocks, the accuracy of satellite-ground time difference measurement link has become the bottleneck of space-based time-frequency distribution. In this paper, the basic principle of two-way time difference measurement is derived. The system error and equipment error involved are analyzed, and the error control strategy is given. The above work will provide engineering guidance for high-precision two-way time difference measurement in the design of satellite-ground links.

Testing is the most important thing to produce a system that is very good and also useful. Pengban a system must be carried out because if there is no prior testing of a system, then what will happen to the system will get a system error that results in a poor quality system and will result in a loss for developers and users. Experiments that have been carried out can find an error, disability, or failure on a system that has been known from the beginning and immediately corrected more thoroughly. In the test there are also types of system experiments, one of which is by testing the black box using an equivalent method that is good for looking for an error on the system. The equivalent method can break down the input domains of the program into a class that can solve test cases. Based on the results of a test that has been done, this application still has an error and also a defect in a system.

Consider the closed-loop control system shown in Fig. 8.1. The open-loop transfer function G(s) is assumed to be given as the cascade connection of the controller Gc(s) and the plant Gp(s), i.e., G(s) = Gc(s)Gp(s). The system error is defined as e(t) = r(t) − c(t), where \(e(t)=\mathcal {L}^{-1}\{E(s)\}\), \(r(t)=\mathcal {L}^{-1}\{R(s)\}\) and \(c(t)=\mathcal {L}^{-1}\{C(s)\}\).

The problems encountered in testing the verification equipment for AC electrical energy meters according to the verification regulation are reviewed and analyzed, and the solutions based on optimizing technologies are proposed within the range permitted by the regulation. A self correction system is developed to improve the output reference conditions. The power stability and the ability to estimate it are improved, by adjusting the frequency and improving computing method. A new type of isolation transformer is designed to eliminate the system error caused by imbalanced transformer load.

The objective of this research was to analyze the factors related to the satisfaction of using smartphones with the Android, iOS and Windows Phone operating systems. The target audience was undergraduates and graduates in courses in the areas of Engineering, Computing and Administration. The database was created through the application of an online questionnaire, based on the Questionnaire for User Interaction Satisfaction - QUIS version 7.0. The interviewees expressed their comfort and acceptability of such systems through grades between 1 and 9 points. The evaluated items were: screen, terminology, learning and system capabilities. A multivariate analysis of the data was applied to obtain the results. The factor analysis and dimensionality reduction by principal component matrix pointed out four new factors that explain 69.2% of the variance of the 21 features initially studied. Issues related to system error messages were the variables with the highest correlation (0.884 and 0.889). The results of this research serve as a guide to new evaluations of operating systems and support for analysis and improvement of usage satisfaction over mobile applications. As recommendations, it is suggested to include new groups of respondents, understanding that factors may interfere or not in the final satisfaction of the users of these platforms. O objetivo desta pesquisa foi analisar os fatores relacionados à satisfação de uso de smartphones com os sistemas operacionais Android, iOS e Windows Phone. O público alvo foram graduandos e graduados em cursos nas áreas de Engenharias, Computação e Administração. A base de dados foi criada por meio da aplicação de um questionário online, fundamentado no Questionnaire For User Interaction Satisfaction - QUIS versão 7.0. Os entrevistados externaram o conforto e aceitabilidade de tais sistemas em notas entre 1 e 9 pontos. Os quesitos avaliados foram: tela, terminologia, aprendizado e recursos do sistema. Foi aplicada uma análise multivariada dos dados para obtenção dos resultados. A análise dos fatores e redução de dimensões por matriz de componentes principais apontou quatro novos fatores que explicam 69.2% da variância das 21 características inicialmente estudadas. Questões relacionadas a mensagens de erro dos sistemas foram as variáveis com maior correlação (0.884 e 0.889). Os resultados desta pesquisa servem como guia de novas avaliações sobre sistemas operacionais e suporte para análise e melhoria de satisfação de uso sobre aplicativos móveis. Como recomendações, sugere-se incluir novos grupos de entrevistados, entendendo que fatores podem interferir, ou não, na satisfação final dos usuários destas plataformas.

As an emerging commercial application, deliveries using Unmanned Aerial Vehicles (UAVs) have the advantages of low cost and flexibility over traditional logistic operations, and are therefore being increasingly adopted by logistics companies. In order to ensure the success of delivery missions, effective traffic management measures, including UAV safety or integrity monitoring, are essential. Currently, however, there is a gap in research on the concept and framework for the evaluation of integrity performance for the delivery application. This paper addresses the issue by proposing a UAV Navigation Monitoring Requirement (UNMR) specification for the monitoring of the accuracy and integrity performance of UAVs for use in delivery applications, based on the concept of Required Navigation Performance (RNP). The method used to determine the position accuracy requirement for en-route and terminal UNMR operations is based on the related factors in the context of UAV-borne delivery. This is represented by the width of the route and radius of the docking or landing spot. Simulation and initial field tests show that the flight technical errors and path definition errors should be considered for the total system error calculation for the UAV delivery. Effective application of the proposed framework for integrity performance evaluation has shown to be of potential benefits for the operational management of UAV deliveries.

Resumen La evaluación fonoaudiológica de la respiración es una herramienta indispensable para el profesional de la salud ya que permite conocer qué dificultades tiene la persona al respirar. Este protocolo en la actualidad se realiza de manera manual con ayuda de pocos marcadores, los cuales no permiten caracterizar la postura corporal, relacionada con distancias, ángulos y posiciones de manera general y segura. Este artículo presenta una novedosa alternativa en el desarrollo de un sistema para mediciones automáticas de variables antropométricas, que intervienen en la evaluación fonoaudiológica de la respiración, usando visión artificial. Se tomaron variables en los 4 planos: frontal, posterior, sagital izquierdo y sagital derecho; igualmente, se incluyeron 32 marcadores para obtener 35 variables antropométricas. El principio de funcionamiento del algoritmo automático para el reconocimiento de variables antropométricas, se probó con dos pacientes, logrando un porcentaje de error general del sistema de 2,81%. Es importante resaltar que este desarrollo permitirá al especialista apoyarse en una herramienta digital para lograr medidas más precisas, mejorando la exactitud y la precisión en el diagnóstico. Abstract The speech-language evaluation of breathing is a tool important for the health professional because it allows to know the difficulties of people when breathing. This protocol is used manually with the help of a few markers, and not allows characterization of body posture, measuring to distances, angles and positions. This article presents a novel alternative in the development of a system for automatic measurements of anthropometric variables, which intervene in the phonoaudiological assessment of respiration, using artificial vision. Variables were taken on the 4 planes: frontal, posterior, left sagittal and right sagittal; Also, 32 markers were included to obtain 35 anthropometric variables. The operating principle of the automatic algorithm for the recognition of anthropometric variables was tested with two patients, achieving an overall system error rate of 2.81%. It is important to emphasize that this development will allow the specialist to rely on a digital tool to achieve more precise measurements, improving accuracy in measurements and diagnosis.

Low-cost sensors are widely used to realize large-scale deployment for sensing systems. In this paper, we discuss challenges in using industrial-grade gas sensors for air quality monitoring. To overcome variation due to system errors, we present a framework for individualized calibration. Within the framework, multiple regression and interpolation methods are prepared for alternative optimization on fitting sensors' response to gas concentration.

Digital image correlation (DIC) method has been applied in wide fields including experimental mechanics. The displacement measurement accuracy plays an important role in these situations. The direct method to improve the measurement accuracy is to reduce the measurement error in DIC. In the paper, a new method has been developed to improve the DIC accuracy using the feature of DIC system error. The feature of DIC system error is analyzed. And the reduction of the DIC system error has been verified by experiment.

How to select optimal ADC parameters in indirect measurement including resolution, sampling rate and sampling error of ADC, and system error is proposed. Fitting of the photo time constant in cavity ring-down spectrum is taken as an example. The effects of resolution, sampling rate and sampling error (with/without system error) of ADC on fitting accuracy are simulated sequentially. The influence of mirror reflectivity on the parameters of fitting functions is analyzed and simulated. Parameters of ADC to distinguish concentration of methane of 1 ppbv at different mirror reflectivity are given.

The radon exhalation rate can be obtained quickly and easily from the evolution of radon concentration over time in the accumulation chamber. Radon monitoring based on the electrostatic collection method is not interfered with by (220)Rn. In this paper, we propose that the difference between radon and (218)Po concentrations in the measurement cell of this kind of radon exhalation monitor is the main system error, and it changes with time and different effective decay constants. Based on the results of simulation experiments, we propose that the calibration factor obtained from the suitable experiment cannot completely correct the system error, even if it is useful to reduce the measurement error. The better way for reducing measurement error is to use the new measurement model which we have proposed in recent years.

In high accuracy radius of curvature (ROC) measurement, discrepancy may exist in results on the same optical surface under different temperature. In this paper, the effects of temperature on ROC are analyzed systematically including system error of interferometry and thermal self-deformation of spherical optical elements. The self-deformation is simulated by finite element analysis method and experiments are carried out on a set of elements with different ROC, repeatedly measured by interferometry. The result shows that the effects of thermal field on ROC augment with the increasing of radius of measured surface and that the experimental results show consistency with the theoretical analysis, thus demonstrating that the effects on ROC can be estimated and compensated under different temperature variation.

The authors report a case in which an intravenous injection of Patent Blue V dye instead of Indigo Carmine was given during routine gynaecological surgery. The patient presented with temporary arterial (spurious) desaturation and skin discoloration over a 48-hour period. Pharmacological differences between these dyes are described. Root cause analysis based on the ALARM (Association of Litigation and Risk Management) model is presented. The authors emphasise that use of this model should not be limited solely to describing and correcting well known systems errors such as working conditions or teamwork and communication. Furthermore, they conclude that insufficient knowledge must also be recognised as a systems error and as such should be sought out and corrected using similar strategies to those used to discover other contributory factors, without allocation of blame to any individual.

This paper proposes a modifled generalized dynamic fuzzy neural network (M-GDFNN) for the application of Adaptive Noise Cancellation (ANC). As system error cannot be evaluated on-line in ANC, †-Completeness of fuzzy rules is selected as the only criteria of fuzzy rules generation in this novel algorithm. To improve system performance, a simple Self-organizing Mapping (SOM) technique is introduced to adjust the center clustering. Additionally, Eigenvalue Decomposition (ED) method is applied to prune unimportant rules. In the last part of this paper, simulation studies illustrate that proposed M-GDFNN is able to achieve better results compared with ANFIS and standard GDFNN in noise cancellation thus prove the suitability of proposed M-GDFNN in the fleld of ANC.

For measurement of existing thread parameters using profile scanning, system error increases as pitch diameter, difference between the calibrating thread and measuring thread increases with the single gauge calibration method. There are several alignment deviations affecting the measurement of pitch diameter. To reduce the system error, a compensation method using two standard thread gauges to calculate the alignment deviations is proposed here. Finally, the theoretical and experimental comparisons between the single gauge calibration method and the proposed method are presented. The results demonstrate that the two gauges calibration method can effectively reduce the system error.

In required navigation performance (RNP), total system error (TSE) is estimated to provide a timely warning in the presence of an excessive error. In this paper, by analyzing the underlying formation mechanism, the TSE estimation is modeled as the estimation fusion of a fixed bias and a Gaussian random variable. To address the challenge of high computational load induced by the accurate numerical method, two efficient methods are proposed for real-time application, which are called the circle tangent ellipse method (CTEM) and the line tangent ellipse method (LTEM), respectively. Compared with the accurate numerical method and the traditional scalar quantity summation method (SQSM), the computational load and accuracy of these four methods are extensively analyzed. The theoretical and experimental results both show that the computing time of the LTEM is approximately equal to that of the SQSM, while it is only about 1/30 and 1/6 of that of the numerical method and the CTEM. Moreover, the estimation result of the LTEM is parallel with that of the numerical method, but is more accurate than those of the SQSM and the CTEM. It is illustrated that the LTEM is quite appropriate for real-time TSE estimation in RNP application.

Aeromagnetic exploration is one of the most important exploration methods in geophysics. In aeromagnetic exploration, three-axis fluxgate magnetometers are widely used to measure the attitude of the platform. However, system error caused by the manufacture precision of three-axis fluxgate magnetometers degrades the measurement accuracy of the attitude. Therefore, the calibration of three-axis fluxgate magnetometers is essential. In this paper, the calibration model of three-axis fluxgate magnetometers is discussed, and the measurement errors of three-axis fluxgate magnetometers in an unmanned helicopter experiment are analyzed. A calibration method is applied to the inflight data. Then, more accurate attitude of the platform is obtained. The validity of the method is demonstrated by the experimental results.

This Quantified System Level Threshold Methodology is a flow that can guide users to use the margin offset function with customer-decided system level stressing to system error found threshold and quantify as how much margin to real system error found threshold for the system configurations that under test. It is able to cover the PVT (Process, Voltage and Temperature) corner cases as well. By adapting this methodology/flow, customers could create their own system dependent system level criteria, POR+ system level criteria and mixed vendors DIMM and mixed vendors registers/buffers DIMM system level criteria by themselves and could deliver more ecosystem friendly systems with higher compatibility to the world.

In this paper, a method of acquisition between optical ground station and quantum communication satellite named Micius for establish optical links is proposed. The acquisition technological specification of the optical ground station system is analyzed. The acquisition strategy of optical ground station is designed. In order to point accurately to quantum satellite for optical ground station, system error modifying method is designed, using the telescope mount model to improve the absolute pointing precision. Finally the experiment result is proposed. Results show that the correction accuracy is better than 5μrad. The acquisition time is less than 5 seconds. © 2017 SPIE.

Strapdown Inertial Navigation System play an important role in many different kinds of applications. As the accuracy of which is deeply influenced by the sensors precision, so the system error propagation should be addressed. Based on the airborne vehicle characteristics, a method based on neural network is proposed to estimate the attitude, velocity and position error of system. The simulation experiment results validate the algorithm in estimate some kind of system errors is better than the traditional method based on Kalman filter model.

From the CMAC basic principle, this paper introduces a kind of CMAC and PID Compound controller, a more detailed introduction to the implementation of this algorithm and the design method; through the given temperature MATALB simulation demonstrates that under certain conditions, the composite controller can be given good temperature tracking, and in the stable, the output of the system error in (−0.05, 0.05), to achieve a better control effect, has certain promotion value.

Higher accuracy of optical surface measurement is needed with the rapid development of optical industry and technology, especially in the field of optical manufacture and optical metrology. Fizeau interferometery is widely recognized as one of the most important measurement techniques currently in use. Results of the Fizeau interferometeric testing contain the reference surface errors and test surface errors. The test accuracy is restricted by the error of reference surface. As a result, so-called absolute flatness testing technology must be used to eliminate the system error such as reference surface error and higher accuracy of the surface profile testing. In this paper, the theory formula of even and odd functions is deduced, and the method are programmed for simulation. Based on HOOL phase-shifting interferometer, experiments are done to achieve high accuracy flatness measurement. The experiment shows that with high-accuracy interferometer, absolute flatness testing technology can effectively calibrate reference surface and improve the accuracy of flatness surface testing. An important result of this experiment is that the accuracy of the test surface can be reached λ/50.

The strapdown fiber optic gyrocompass (strapdown FOGC) system for ships primarily works on external horizontal damping and undamping statuses. When there are large sea condition changes, the system will switch frequently between the external horizontal damping status and the undamping status. This means that the system is always in an adjustment status and influences the dynamic accuracy of the system. Aiming at the limitations of the conventional damping method, a new design idea is proposed, where the adaptive control method is used to design the horizontal damping network of the strapdown FOGC system. According to the size of acceleration, the parameters of the damping network are changed to make the system error caused by the ship’s maneuvering to a minimum. Furthermore, the jump in damping coefficient was transformed into gradual change to make a smooth system status switch. The adaptive damping network was applied for strapdown FOGC under the static and dynamic condition, and its performance was compared with the conventional damping, and undamping means. Experimental results showed that the adaptive damping network was effective in improving the dynamic performance of the strapdown FOGC.