Effect Of Such Errors Research Articles

How Important are Detailed Hand Motions for Communication for a Virtual Character Through the Lens of Charades?

Detailed hand motions play an important role in face-to-face communication to emphasize points, describe objects, clarify concepts, or replace words altogether. While shared virtual reality (VR) spaces are becoming more popular, these spaces do not, in most cases, capture and display accurate hand motions. In this article, we investigate the consequences of such errors in hand and finger motions on comprehension, character perception, social presence, and user comfort. We conduct three perceptual experiments where participants guess words and movie titles based on motion captured movements. We introduce errors and alterations to the hand movements and apply techniques to synthesize or correct hand motions. We collect data from more than 1000 Amazon Mechanical Turk participants in two large experiments, and conduct a third experiment in VR. As results might differ depending on the virtual character used, we investigate all effects on two virtual characters of different levels of realism. We furthermore investigate the effects of clip length in our experiments. Amongst other results, we show that the absence of finger motion significantly reduces comprehension and negatively affects people’s perception of a virtual character and their social presence. Adding some hand motions, even random ones, does attenuate some of these effects when it comes to the perception of the virtual character or social presence, but it does not necessarily improve comprehension. Slightly inaccurate or erroneous hand motions are sufficient to achieve the same level of comprehension as with accurate hand motions. They might however still affect the viewers’ impression of a character. Finally, jittering hand motions should be avoided as they significantly decrease user comfort.

When facial recognition does not ‘recognise’: erroneous identifications and resulting liabilities

Facial recognition is an artificial intelligence-based technology that, like many other forms of artificial intelligence, suffers from an accuracy deficit. This paper focuses on one particular use of facial recognition, namely identification, both as authentication and as recognition. Despite technological advances, facial recognition technology can still produce erroneous identifications. This paper addresses algorithmic identification failures from an upstream perspective by identifying the main causes of misidentifications (in particular, the probabilistic character of this technology, its ‘black box’ nature and its algorithmic bias) and from a downstream perspective, highlighting the possible legal consequences of such failures in various scenarios (namely liability lawsuits). In addition to presenting the causes and effects of such errors, the paper also presents measures that can be deployed to reduce errors and avoid liabilities.

Anomalous Small-Angle X-Ray Scattering of Fuel-Cell Catalyst Samples

Anomalous small-angle X-ray scattering (ASAXS) is a technique capable of extracting element-specific structural information from multi-element materials, and is considered useful in the structure analysis of metal alloy catalyst particles for fuel cells. ASAXS utilizes the resonant term of the atomic scattering factor of the element of interest. The resonant term has a real part (f1) and an imaginary part (f2), and f1 mainly contributes to the anomalous scattering phenomenon. The amplitude of f1 varies with X-ray energy, and decreases sharply around the absorption edges of the element. The decrease is as large as -18 electrons in the case of platinum (Pt) LIII-edge. ASAXS experiments are possible only in synchrotron radiation facilities where X-ray energies are freely tunable.ASAXS experiments require X-ray recordings at 3 or more different X-ray energies to mathematically isolate the element-specific component. Although the energy dependence of f1 seems substantial at around the absorption edge, its contribution to the total scattering intensity from a multi-element system is subtle, and high-precision measurements are required to obtain correct structural information.In actual measurements, experimental errors can arise from many sources, even in present-day third-generation synchrotron radiation facilities. They include fluctuations of the X-ray beam intensities and positions, the calibration error of X-ray energies, and time-dependent changes of sample properties. Here we evaluate the effect of such errors by using model calculations. The model consists of a mixture of 3-nm Pt particles and 5-nm gold (Au) nanoparticles.The scattering profiles of this mixture were calculated for X-ray energies of 11.504, 11.555 and 11.560 keV (Curve A in Figure 1. The LIII edge is at 11.564 keV). The scattering amplitude of the Pt particles was calculated by using the f1 and f2 values from the Cromer-Liberman tables (Brennan & Cowan, Rev. Sci. Instr., 63, 1992), using equations described by Sanada et al. (J. Am. Chem. Soc., 135, 2013). The scattering from Au particles (Curve B) was assumed to be independent of energy. The extracted scattering profile for Pt was identical to that calculated for a sample with Pt particles alone (Curve D, compare with C). Next, the scattering intensities at a specific energy were deliberately changed by a few percent before extracting the Pt contribution. For intensities at 11.56 keV, even a reduction of as slight as 0.2% resulted in catastrophic consequences (Curve F). With a 5% increase of intensity, the generated Pt profile superficially looked normal, but in reality the scattering curve retained the features of the Pt-Au mixture, meaning that the Pt-specific component was not successfully extracted (Curve D).These results indicates that the accuracy requirements in ASAXS measurements are very stringent, and every effort should be made to eliminate factors that can cause errors and uncertainties.In the meeting, data recorded from actual catalyst samples will also be presented, including those from MIRAI (fuel-cell vehicle manufactured by Toyota).This work was performed under the NEDO FC-Platform project. Figure 1

Validity of data extraction in evidence synthesis practice of adverse events: reproducibility study.

ObjectivesTo investigate the validity of data extraction in systematic reviews of adverse events, the effect of data extraction errors on the results, and to develop a classification framework for data extraction errors to support further methodological research.DesignReproducibility study.Data sourcesPubMed was searched for eligible systematic reviews published between 1 January 2015 and 1 January 2020. Metadata from the randomised controlled trials were extracted from the systematic reviews by four authors. The original data sources (eg, full text and ClinicalTrials.gov) were then referred to by the same authors to reproduce the data used in these meta-analyses.Eligibility criteria for selecting studiesSystematic reviews were included when based on randomised controlled trials for healthcare interventions that reported safety as the exclusive outcome, with at least one pair meta-analysis that included five or more randomised controlled trials and with a 2×2 table of data for event counts and sample sizes in intervention and control arms available for each trial in the meta-analysis.Main outcome measuresThe primary outcome was data extraction errors summarised at three levels: study level, meta-analysis level, and systematic review level. The potential effect of such errors on the results was further investigated.Results201 systematic reviews and 829 pairwise meta-analyses involving 10 386 randomised controlled trials were included. Data extraction could not be reproduced in 1762 (17.0%) of 10 386 trials. In 554 (66.8%) of 829 meta-analyses, at least one randomised controlled trial had data extraction errors; 171 (85.1%) of 201 systematic reviews had at least one meta-analysis with data extraction errors. The most common types of data extraction errors were numerical errors (49.2%, 867/1762) and ambiguous errors (29.9%, 526/1762), mainly caused by ambiguous definitions of the outcomes. These categories were followed by three others: zero assumption errors, misidentification, and mismatching errors. The impact of these errors were analysed on 288 meta-analyses. Data extraction errors led to 10 (3.5%) of 288 meta-analyses changing the direction of the effect and 19 (6.6%) of 288 meta-analyses changing the significance of the P value. Meta-analyses that had two or more different types of errors were more susceptible to these changes than those with only one type of error (for moderate changes, 11 (28.2%) of 39 v 26 (10.4%) 249, P=0.002; for large changes, 5 (12.8%) of 39 v 8 (3.2%) of 249, P=0.01).ConclusionSystematic reviews of adverse events potentially have serious issues in terms of the reproducibility of the data extraction, and these errors can mislead the conclusions. Implementation guidelines are urgently required to help authors of future systematic reviews improve the validity of data extraction.

On the identification of the probability density function of a dimension from data with measurement errors

Metrology tools are applicable to check whether dimensions lay within their tolerance intervals. However, measurement errors cannot be avoided. This paper develops a method to partially correct the effect of such errors in case their probability density function is known. We assume that the probability density function associated with the measured dimension is available, for instance identified after multiple parts are manufactured and their dimension is measured. In this context, the probability density function of the measured value is the convolution product between the probability density functions of the measurement error and of the true value, respectively. Therefore, characterizing the true value is a challenging task, as this involves a deconvolution. We propose a procedure based on: (i) the transformation of the integral involved in the convolution product into a sum using numerical integration; (ii) the definition of a set of non-linear equalities solved using Newton-Raphson's procedure. An application example is used to discuss the relevance of the proposed method and the influence of various parameters on the results.

Simulating systematic bias in attributed social networks and its effect on rankings of minority nodes

Network analysis provides powerful tools to learn about a variety of social systems. However, most analyses implicitly assume that the considered relational data is error-free, and reliable and accurately reflects the system to be analysed. Especially if the network consists of multiple groups (e.g., genders, races), this assumption conflicts with a range of systematic biases, measurement errors and other inaccuracies that are well documented in the literature. To investigate the effects of such errors we introduce a framework for simulating systematic bias in attributed networks. Our framework enables us to model erroneous edge observations that are driven by external node attributes or errors arising from the (hidden) network structure itself. We exemplify how systematic inaccuracies distort conclusions drawn from network analyses on the task of minority representations in degree-based rankings. By analysing synthetic and real networks with varying homophily levels and group sizes, we find that the effect of introducing systematic edge errors depends on both the type of edge error and the level of homophily in the system: in heterophilic networks, minority representations in rankings are very sensitive to the type of systematic edge error. In contrast, in homophilic networks we find that minorities are at a disadvantage regardless of the type of error present. We thus conclude that the implications of systematic bias in edge data depend on an interplay between network topology and type of systematic error. This emphasises the need for an error model framework as developed here, which provides a first step towards studying the effects of systematic edge-uncertainty for various network analysis tasks.

Assessing errors during simulation configuration in crop models – A global case study using APSIM-Potato

Crop models are usually developed using a test set of data and simulations representing a range of environment, soil, management and genotype combinations. Previous studies demonstrated that errors in the configuration of test simulations and aggregation of observed data sets are common and can cause major problems for model development. However, the extent and effect of such errors using Agricultural Production system SIMulator Next Generation (APSIM) crop models are not usually considered as a source of model uncertainty. This is a methodological paper describing several approaches for testing the APSIM simulation configuration to detect anomalies in the input and observed data. In this study, we assess the simulation configuration process through (i) quality control analysis based on a standardised climate dataset (ii) outlier identification and (iii) a palette of visualization tools. A crop model – APSIM-Potato is described to demonstrate the main sources of error during the simulation configuration and data collation processes. Input data from 426 experiments conducted from 1970 to 2019 in 19 countries were collected and configured to run a model simulation. Plots were made comparing simulation configuration data and observed data across the entire test set so these values could be checked relative to others in the test set and with independent datasets. Errors were found in all steps of the simulation configuration process (climate, soil, crop management and observed data). We identified a surprising number of errors and inappropriate assumptions that had been made which could influence model predictions. The approach presented here moved the bulk of the effort from fitting model processes to setting up broad simulation configuration testing and detailed interrogation to identify current gaps for further model development.

Robustness of Real-Time Heuristic Search Algorithms to Read/Write Error in Externally Stored Heuristics

Real-time heuristic search algorithms follow the agent-centered search paradigm wherein the agent has access only to information local to the agent’s current position in the environment. This allows agents with constant-bounded computational faculties (e.g., memory) to take on search problems of progressively increasing sizes. As the agent’s memory does not scale with the size of the search problem, the heuristic must necessarily be stored externally, in the environment. Storing the heuristic in the environment brings the extra challenge of read/write errors. In video games, introducing error artificially to the heuristics can make the non-player characters (NPC) behave more naturally. In this paper, we evaluate effects of such errors on real-time heuristic search algorithms. In particular, we empirically study the effects of heuristic read redundancy on algorithm performance and compare its effects to the existing technique of using weights in heuristic learning. Finally, we evaluate a recently proposed technique of correcting the heuristic with a one-step error term in the presence of read/write error.

Influence of Errors in Known Constants and Boundary Conditions on Solutions of Inverse Heat Conduction Problem

This work examines the effects of the known boundary conditions on the accuracy of the solution in one-dimensional inverse heat conduction problems. The failures in many applications of these problems are attributed to inaccuracy of the specified constants and boundary conditions. Since the boundary conditions and material properties in most thermal problems are imposed with uncertainty, the effects of their inaccuracy should be understood prior to the inverse analyses. The deviation from the exact solution has been examined for each case according to the errors in material properties, boundary location, and known boundary conditions. The results show that the effects of such errors are dramatic. Based on these results, the applicability and limitations of the inverse heat conduction analyses have been evaluated and discussed.

Errors in nurse-led triage: An observational study

BackgroundNurses play a crucial role in correctly prioritizing patients entering emergency departments. However, little is known of the accuracy of nurse-led triage systems. Objectives(1) To determine the frequency of nurse-led triage errors within the Manchester Triage System; (2) to explore patient, work environment and individual nurse factors associated with triage errors; and (3) to explore associations between triage errors and patient outcomes (i.e., length of emergency department stay, hospitalization, and 7- and 30-day mortality). SettingThis study was conducted in one emergency department in Northern Italy. ParticipantsA random sample of 5% (n = 1,929) of all eligible patients accessing the emergency department over an 18-month period. MethodsFor this retrospective observational study, electronic health record data on triage errors (i.e., incorrect presentational flowchart, specific discriminator and/or priority level) and triage nurses were combined with routine data on patient characteristics, outcomes and the work environment. To explore relationships between these variables, we performed univariate and multivariate logistic regression analyses. ResultsWe observed triage errors in 16.3% of patients (n = 314). These were significantly associated with patients’ emergency department and hospital stays. Analyses revealed that when > one patient was triaged every 15 min (OR: 2.112;95%CI: 1.331–3.354), older patients (OR: 1.009; 95%CI: 1.003–1.015) with > than two chronic conditions (OR: 1.506; 95%CI: 1.091–2.081) and orange or red priority codes (OR: 1.314; 95%CI: 1.046–1.651,) whose triage nurse had previous experience with another triage system (OR: 3.189; 95%CI: 2.455–4.14) had higher odds of triage errors. ConclusionWe provided primary evidence on triage errors. Confirming our findings on the prevalence, nature and consequences of such errors will require further prospective multicenter studies. Considering patient factors (e.g., age, polychronicity) as additional discriminators could make the nurse-led triage process using the Manchester Triage System more accurate. Investigating the roles of triage nurses’ training and background and the emergency department work environment on their mental models regarding the triage process will require qualitative research.

Typical errors and violations of biotechnics of artificial breeding of pacific salmon

In two parts of the article, more than 70 errors and violations of the Biotechnics of artificial breeding of Pacific salmon in salmon hatcheries are collected and summarized, which lead to an immediate or delayed deterioration of the quality of reared fry and a decrease in their survival rate. Deviations from the biological basis of fish farming are shown and possible consequences of such errors or violations are predicted. In the first part of the article (#7,2020) there were General errors (throughout the entire fish-breeding process), as well as violations of Biotechnics during the work with producers, collecting eggs and preparing them for incubation, in the second part-violations of Biotechnics during the incubation of eggs, holding pre-larvae, rearing and release of young. Their correction, prevention or minimization of consequences will significantly improve the quality of sexual products and offspring from producers, increase the linear and weight gain of juveniles during rearing, improve the coefficient of feed payment, reduce the time of rearing, improve the epizootic situation by developing immunity in fry and mobilizing other protective reactions of their body, significantly reduce waste at all stages of the production process, increasing survival by 10–15%. In conclusion, it is noted that the first and most important condition for an efficient salmon hatchery is the creation of optimal environmental conditions at each stage of the production process. The second condition is strict compliance with the Biotechnics of artificial salmon breeding and the complex of veterinary and sanitary, fish-breeding and meliorative and therapeutic and preventive measures. The third is the availability of competent specialists who regularly improve their skills in accredited Universities to implement, control and manage the first two conditions.

Typical errors and violations of biotechnics of artificial breeding of pacific salmon. Part 1

The article contains and summarizes typical biotechnical errors and violations that are made on a daily and routine basis by fish breeders. Deviations from the biological basis of fish breeding are also shown and possible consequences of such errors or violations are predicted. Their correction, prevention or minimization of consequences, will significantly improve the quality of sexual products and offspring from producers, increase the linear and weight gain of juveniles during rearing, improve the feed payment coefficient, reduce the time of rearing, improve the epizootic situation by developing immunity in fry and mobilizing other protective reactions of their body, significantly reduce waste at all stages of the production process, increasing the survival rate of fry by 10–15 %.

Articulation of the problem of ensuring security of the algorithms of intelligent systems

Relevance of the selected topic is defined by implementation of autonomous robotic systems of various designation. The object of this research is the algorithmic problems emerging in monitoring the security of algorithms. The author determines the existing contradiction between the need for automation of robotics and the complexity of software implementation of this requirement. The research is carried out on the example of implementation of robotics in transport and military spheres. Realization of the trends of automation in these spheres generates certain legal and technological problems associated with algorithmic support of the autonomous systems. The indicated problems manifest in unrecoverable application errors, divided by the experts into the errors of first and second grade. The primary cause for the occurrence of such errors in robotics consists in misuse of autonomous robotic systems software. If for conventional technical systems the consequences of such errors and responsibility thereof are predictable, the problem of implementation of the autonomous robots needs to be addressed. Using the general scientific methods of analysis and synthesis, the author examines the key aspects of the current state and prospects of algorithmization of usage of autonomous systems. Leaning on the general review of algorithmic problems of implementation of autonomous robots, implications and manifestation of errors of first and second grade emerging in their implementation, the author synthesizes articulation of the scientific problem of division of responsibility between the developers and the users of systems in the context of elaboration of algorithms of their implementation,

THE CONCEPT, ESSENCE AND CONTENT OF ADMINISTRATIVE MISTAKE IN THE ACTIVITIES OF PUBLIC AUTHORITIES

Introduction. Public authorities, officials, civil servants in carrying out administrative activities, in some cases may violate the principle of legality of public administration, carry out erroneous administrative actions, adopt unreasonable and illegal administrative acts. These negative results of executive and administrative activities of officials violate the rights and freedoms of man and citizen, the legitimate interests of public organizations and legal entities. Such phenomena are called "administrative error". The purpose of the article is to develop theoretical and legal bases of administrative error in the activities of public authorities. Research methods. During the analysis of the essence and content of the administrative error, general scientific methods were used, which are based on the method of dialectics, and especially scientific methods of legal knowledge (formal-logical, system-structural). Summary of the main results. The article is devoted to the analysis and research of the concept of administrative error in various legal spheres. The question of studying the causes and consequences of such errors is relevant today, as Ukraine is still reforming the administrative system and changes in the system of public authorities and public administration. These processes, under the influence of administrative reform, have shown not only declarative intentions to transform these relations towards democratic ones, but also a real desire to change the system of public administration to European standards. Therefore, the process of development of public administration was one of the defining components of the overall vector to a democratic, social and legal state. During the exercise of powers by public authorities, officials and civil servants, the action or inaction of governmental subjects of administrative law may be allowed, which leads to violation of human and civil rights and freedoms, legitimate interests of public organizations and legal entities. The consequences of their actions, which lead to administrative errors, are particularly severe, as they violate key principles of public administration, legal rights and individual freedoms, and diminish the authority of public authorities. An imperfect system of mechanisms for the occurrence, detection and prevention of administrative errors is a significant barrier to ensuring a modern system of good governance. Because administrative errors of public authorities are a serious political and socio-legal problem of assumptions, which demonstrate the legal insecurity of man and citizen. Conclusions. Creating an effective mechanism for detecting, preventing and correcting administrative errors could be crucial to reforming the system of public administration in line with modern European values.

Measurement error in a multi-level analysis of air pollution and health: a simulation study

BackgroundSpatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health.MethodsOur study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of “true” site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009–2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and “true” data and the ratio of their variances (model versus “true”) and assumed these parameters were the same spatially and temporally.ResultsIn general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1.ConclusionWhile our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and “true” data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models.

Relationship between Omission, Commission Errors and Number of Drugs Prescribed

Background and Aims: Medication prescribing error is common, the consequences of such errors are more harmful and frequent among patients in the hospital, the specific aim of the study was identify types of prescribing errors, identify the most common drugs prescribed in the hospitals and to see if there is correlation between the numbers of drugs prescribed and the number errors (omissions and commissions). Method: Prospective cross-sectional study was performed in the security force clinics in Riyadh, The 300 prescriptions were collected from the central pharmacy with convenience sampling procedure to select the prescriptions and the study used a descriptive and inferential analysis to answer the research questions. Results: A total of 759 drugs were prescribed, in which 4118 errors were discovered in the prescriptions (2408 omissions errors, 1710 commissions errors), the most common omissions errors in the prescription under study was omit patient gender, in which nearly all the prescription didn’t determine the gender of patients, following by omit name of department 298 (99.3%), the most common commission errors was illegible writing 650 (86%) in the prescriptions under study, following by omit strength of drugs 464 (61.4%), omit route of drugs administrations 417 (55.2%), the most common drugs prescribed through the study periods were analgesics 203 (26.9%) and the second highest category of drugs were antibiotics (antibacterial) 136 (18%), the most common drugs subjected to prescribing errors were analgesic 27.10%, antibiotics 15.20% and bronchodilators 10.70%, there is a strong positive correlation between the number of drugs prescribed and the number of commission errors. Conclusion: Application of modification prescriptions forms, structured prescribing training program, strict legislation measures relating to drugs prescriptions and development of system by applying CPOE and CDSS are among the necessary intervention (s) that may reduce the prescription errors, increase the patient safety and protect them from medication errors.

English

Project management is one of the most important and poorly understood areas of management. Delays and cost overruns are common in projects such as construction, power generation, defense, software, product development, etc. Project management is affected by problems relating to costing and scheduling. Changes in the design of customer creates costly ripple effects which in turn lead to delay and disruption throughout an entire organization. In most cases, errors made earlier in engineering projects are discovered close to the end which may require costly rework, expediting, overtime, hiring, schedule slippage or reductions in project scope or quality. Poor profitability, loss of market share and reputation, increased turnover of management and workforce, lower productivity and higher costs are some of the effects of such errors. Other consequences include divisive and costly ligation between customers and contractors over responsibility for overruns and delays. This paper describes in brief, the relevance of modeling and simulation in the management of engineering projects with a case study in the oil and gas industry. Key words: Engineering management, modeling, project management, simulation applications, facility management.

Atomic clock ensemble in space (ACES) data analysis

The Atomic Clocks Ensemble in Space (ACES/PHARAO mission, ESA & CNES) will be installed on board the International Space Station (ISS) next year. A crucial part of this experiment is its two-way microwave link (MWL), which will compare the timescale generated on board with those provided by several ground stations disseminated on the Earth. A dedicated data analysis center is being implemented at SYRTE—Observatoire de Paris, where our team currently develops theoretical modelling, numerical simulations and the data analysis software itself.In this paper, we present some key aspects of the MWL measurement method and the associated algorithms for simulations and data analysis. We show the results of tests using simulated data with fully realistic effects such as fundamental measurement noise, Doppler, atmospheric delays, or cycle ambiguities. We demonstrate satisfactory performance of the software with respect to the specifications of the ACES mission. The main scientific product of our analysis is the clock desynchronisation between ground and space clocks, i.e. the difference of proper times between the space clocks and ground clocks at participating institutes. While in flight, this measurement will allow for tests of general relativity and Lorentz invariance at unprecedented levels, e.g. measurement of the gravitational redshift at the level.As a specific example, we use real ISS orbit data with estimated errors at the 10 m level to study the effect of such errors on the clock desynchronisation obtained from MWL data. We demonstrate that the resulting effects are totally negligible.

Mannequin-Based Teaching to Reinforce the Concept of Intravenous Administration in 2nd Year MBBS Students

Drug administration errors account for 15.34% of all medication errors. The financial consequences of such errors are tremendous and, could in fact, directly influence the cost of healthcare. Wrong dilutions and wrong IV infusion speed, improper dose/quantity due to wrong dose calculation and so on are the various types of drug administration errors that occur during parenteral administration.

Generalized stability estimates in inverse transport theory

Inverse transport theory concerns the reconstruction of the absorption and scattering coefficients in a transport equation from knowledge of the albedo operator, which models all possible boundary measurements. Uniqueness and stability results are well known and are typically obtained for errors of the albedo operator measured in the \begin{document} $L^1$ \end{document} sense. We claim that such error estimates are not always very informative. For instance, arbitrarily small blurring and misalignment of detectors result in \begin{document} $O(1)$ \end{document} errors of the albedo operator and hence in \begin{document} $O(1)$ \end{document} error predictions on the reconstruction of the coefficients, which are not useful. This paper revisit such stability estimates by introducing a more forgiving metric on the measurements errors, namely the \begin{document} $1-$ \end{document} Wasserstein distances, which penalize blurring or misalignment by an amount proportional to the width of the blurring kernel or to the amount of misalignment. We obtain new stability estimates in this setting. We also consider the effect of errors, still measured in the \begin{document} $1-$ \end{document} Wasserstein distance, on the generation of the probing source. This models blurring and misalignment in the design of (laser) probes and allows us to consider discretized sources. Under appropriate assumptions on the coefficients, we quantify the effect of such errors on the reconstructions.