Journal articles: 'Computer errors'

1

Elliot, Rod. "Computer errors." New Scientist 215, no. 2875 (July 2012): 27. http://dx.doi.org/10.1016/s0262-4079(12)61952-6.

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Porsani, Milton J., and Bjørn Ursin. "Direct multichannel predictive deconvolution." GEOPHYSICS 72, no. 2 (March 2007): H11—H27. http://dx.doi.org/10.1190/1.2432260.

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The Levinson principle generally can be used to compute recursively the solution of linear equations. It can also be used to update the error terms directly. This is used to do single-channel deconvolution directly on seismic data without computing or applying a digital filter. Multichannel predictive deconvolution is used for seismic multiple attenuation. In a standard procedure, the prediction-error filter matrices are computed with a Levinson recursive algorithm, using a covariance matrix of the input data. The filtered output is the prediction errors or the nonpredictable part of the data. Starting with the classical Levinson recursion,wehave derived new algorithms for direct recursive calculationof the prediction errors without computing the data covariance-matrix or computing the prediction-error filters. One algorithm generates recursively the one-step forward and backward predic-tion errors and the L-step forward prediction error, computing only the filter matrices with the highest index. A numerically more stable algorithm uses reduced QR decomposition or singular-value decomposition (SVD) in a direct recursive computation of the prediction errors without computing any filter matrix. The new, stable, predictive algorithms require more arithmetic opera-tions in the computer, but the computer programs and data flow are much simpler than for standard predictive deconvolution.

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RuDusky, Basil M., and Basil M. RuDusky. "Errors of Computer Electrocardiography." Angiology 48, no. 12 (December 1997): 1045–50. http://dx.doi.org/10.1177/000331979704801204.

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Hurst, J. Willis, Charles B. Treasure, and Charn S. Sathavorn. "Computer errors in electrocardiography." Clinical Cardiology 19, no. 7 (July 1996): 580–86. http://dx.doi.org/10.1002/clc.4960190711.

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Correia, John A., Nathaniel M. Alpert, Richard B. Buxton, and Robert H. Ackerman. "Analysis of Some Errors in the Measurement of Oxygen Extraction and Oxygen Consumption by the Equilibrium Inhalation Method." Journal of Cerebral Blood Flow & Metabolism 5, no. 4 (December 1985): 591–99. http://dx.doi.org/10.1038/jcbfm.1985.88.

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Some sources of error in the equilibrium inhalation method for the measurement of oxygen extraction fraction and CMRO2 by positron emission computed tomography scanning have been evaluated by computer simulation. Emphasis has been placed on errors that have not been thoroughly studied in past work. These include effects of random statistical errors, systematic errors in arterial blood radioactivity concentrations, and errors due to perturbations of the equilibrium state, to tissue inhomogeneity, and to subject motion.

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Qin, Li Juan. "Robustness Problem Argumentation from Image Quantization Errors in Vision Location." Advanced Materials Research 225-226 (April 2011): 1332–35. http://dx.doi.org/10.4028/www.scientific.net/amr.225-226.1332.

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In our vision location system, error is inevitable. Image quantization errors play an important role in computer vision field. Quantization errors are the primary sources that affect the precision of pose estimation and they are inherent and unavoidable. It is important to analysis on the effect of this error on compute process. In this paper, Robustness problem argumentation in vision location is presented in detail. Then we introduce image quantization error. Robustness mathematical model for vision location is set up at last.

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SNAPPER, JOHN W. "RESPONSIBILITY FOR COMPUTER-BASED ERRORS." Metaphilosophy 16, no. 4 (October 1985): 289–95. http://dx.doi.org/10.1111/j.1467-9973.1985.tb00175.x.

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RuDusky, Basil M. "Errors of Computer Electrocardiography Revisited." Angiology 64, no. 8 (August 5, 2013): 646–47. http://dx.doi.org/10.1177/0003319712470487.

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Otte, George. "Computer-Adjusted Errors and Expectations." Journal of Basic Writing 10, no. 2 (1991): 71–86. http://dx.doi.org/10.37514/jbw-j.1991.10.2.05.

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Turner, Jerry L. "The Impact of Materiality Decisions on Financial Ratios: A Computer Simulation." Journal of Accounting, Auditing & Finance 12, no. 2 (April 1997): 125–47. http://dx.doi.org/10.1177/0148558x9701200202.

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This study examines the extent to which immaterial uncorrected errors may combine to affect specific financial ratios. A simulation is performed in which three balance sheet accounts and three related income statement accounts are seeded with immaterial errors. The magnitudes of the errors are controlled so the financial statement account balances are materially correct both individually and in the aggregate. The study examines six materiality heuristics for each of three industry classifications and three different error distribution patterns. For each heuristic/industry combination and error distribution pattern, a 95 percent confidence interval is generated for nine financial ratios. Results indicate that immaterial errors may combine to create substantial variances in some ratios. Profitability ratios based on income statement accounts display wide confidence intervals, while solvency ratios based on balance sheet accounts display relatively narrow intervals. Comparison between a standard normal distribution and a nonsymmetrical error distribution indicates that ratio variances are substantial and sensitive to error patterns even when errors are immaterial. Tests for equality of variances identify significant differences between heuristic methods and between industries. When making the decision regarding requiring entry or waiving discovered errors, the auditor should consider the impact of such errors not only on financial statement balances, but on the ways users may combine those balances.

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Owen, Charles B., Laura Dillon, Alison Dobbins, Matthew Rhodes, Madeline Levinson, and Noah Keppers. "Computer literacy through dance: the dancing computer project." International Journal of Pervasive Computing and Communications 13, no. 1 (April 3, 2017): 26–40. http://dx.doi.org/10.1108/ijpcc-02-2017-0012.

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Purpose The purpose of this paper is to present the design and evolution of the Dancing Computer project. Dancing Computer is an ongoing research project at the Michigan State University, which is developing a system that aims to increase computer literacy in elementary-aged children by teaching them first to read code before they write it. The main objective is to educate children on basic concepts of computer science. Design/methodology/approach Children are given tablet computers that present a simple program line-by-line that they execute as they pretend to be a computer. The programs are acted out on a portable dance floor consisting of colored tiles, and the program statements instruct the child to move, turn and act out dance poses and terminology. Findings The Dancing Computer prototype was tested in six different locations in 2016, reaching approximately 250 students. Learning was demonstrated by significant improvements in both task duration and error performance as students performed the activities. The most common errors were movement errors, where participants failed to move the correct number of squares. Social implications This project has the potential to increase the level of computer literacy for thousands of children. This project’s goal is to increase understanding of what a computer does, what a program does and the step-by-step nature of computer programs. Originality/value This is a unique and a different approach – the norm being to start students off writing code in some language. In Dancing Computer stages children as readers of programs, allowing them to pretend to be a computer in a fun and engaging activity while also learning how computers execute real programs.

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Allen, Brian C., Edward Florez, Reza Sirous, Seth T. Lirette, Michael Griswold, Erick M. Remer, Zhen J. Wang, et al. "Comparative Effectiveness of Tumor Response Assessment Methods: Standard of Care Versus Computer-Assisted Response Evaluation." JCO Clinical Cancer Informatics, no. 1 (November 2017): 1–16. http://dx.doi.org/10.1200/cci.17.00026.

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Purpose To compare the effectiveness of metastatic tumor response evaluation with computed tomography using computer-assisted versus manual methods. Materials and Methods In this institutional review board–approved, Health Insurance Portability and Accountability Act–compliant retrospective study, 11 readers from 10 different institutions independently categorized tumor response according to three different therapeutic response criteria by using paired baseline and initial post-therapy computed tomography studies from 20 randomly selected patients with metastatic renal cell carcinoma who were treated with sunitinib as part of a completed phase III multi-institutional study. Images were evaluated with a manual tumor response evaluation method (standard of care) and with computer-assisted response evaluation (CARE) that included stepwise guidance, interactive error identification and correction methods, automated tumor metric extraction, calculations, response categorization, and data and image archiving. A crossover design, patient randomization, and 2-week washout period were used to reduce recall bias. Comparative effectiveness metrics included error rate and mean patient evaluation time. Results The standard-of-care method, on average, was associated with one or more errors in 30.5% (6.1 of 20) of patients, whereas CARE had a 0.0% (0.0 of 20) error rate ( P < .001). The most common errors were related to data transfer and arithmetic calculation. In patients with errors, the median number of error types was 1 (range, 1 to 3). Mean patient evaluation time with CARE was twice as fast as the standard-of-care method (6.4 minutes v 13.1 minutes; P < .001). Conclusion CARE reduced errors and time of evaluation, which indicated better overall effectiveness than manual tumor response evaluation methods that are the current standard of care.

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Pezeshki, Mostafa, and Behrooz Arezoo. "Accuracy enhancement of kinematic error model of three-axis computer numerical control machine tools." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 231, no. 11 (January 5, 2016): 2021–30. http://dx.doi.org/10.1177/0954405415619872.

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Accurate estimation of volumetric errors is an important issue in machining operations. For this purpose, a kinematic error model is used to characterize machine tool’s related errors on its workspace. In this research, it is shown that when measuring the linear and positioning errors using a laser interferometer, part of the angular errors are converted to linear and positioning errors and their magnitudes are overestimated. These values are calculated twice in the models which use homogeneous transformation matrix since Abbe’s principle is not considered. In this article, a kinematic error model is proposed which eliminates this overestimation. This model’s methodology is based on rigid body kinematic and errors measurement by laser interferometer and can be generalized for all three-axis machine tools. A software package is developed to integrate the kinematic errors with the NC-codes. A workpiece is machined in the virtual environment and compared with a workpiece machined in real environment. It is shown that the kinematic error model developed in this research predicts the kinematic errors more accurately.

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Allen, Brian, Edward Florez, Reza Sirous, Seth T. Lirette, Michael Griswold, Erick M. Remer, Zhen J. Wang, et al. "Comparative effectiveness of tumor response assessment methods: Standard-of-care versus computer-assisted response evaluation." Journal of Clinical Oncology 35, no. 6_suppl (February 20, 2017): 432. http://dx.doi.org/10.1200/jco.2017.35.6_suppl.432.

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432 Background: In clinical trials and clinical practice, tumor response assessment with computed tomography (CT) defines critical end points in patients with metastatic disease treated with systemic agents. Methods to reduce errors and improve efficiency in tumor response assessment could improve patient care. Methods: Eleven readers from 10 different institutions independently categorized tumor response according to three different therapeutic response criteria using paired baseline and initial post-therapy CT studies from 20 randomly selected patients with metastatic renal cell carcinoma treated with sunitinib as part of a completed phase III multi-institutional study. Images were evaluated with a manual tumor response evaluation method (standard-of-care) and with computer-assisted response evaluation (CARE) that included stepwise guidance, interactive error-identification and correction methods, automated tumor metric extraction, calculations, response categorization, and data/image archival. A cross-over design, patient randomization, and two-week washout period were used to reduce recall bias. Comparative effectiveness metrics included error rate and mean patient evaluation time. Results: The standard-of-care method was on average associated with one or more errors in 30.5% (6.1/20) of patients while CARE had a 0.0% (0.0/20) error rate (p<0.001). The most common errors were related to data transfer and arithmetic calculation. In patients with errors, the median number of error types was 1 (range 1-3). Mean patient evaluation time with CARE was twice as fast as the standard-of-care method (6.4 vs. 13.1 minutes, p<0.001). Conclusions: Computer-assisted tumor response evaluation reduced errors and time of evaluation, indicating better overall effectiveness than manual tumor response evaluation methods that are the current standard-of-care.

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Yang, Hongtao, Mei Shen, Li Li, Yu Zhang, Qun Ma, and Mengyao Zhang. "New identification method for computer numerical control geometric errors." Measurement and Control 54, no. 5-6 (May 2021): 1055–67. http://dx.doi.org/10.1177/00202940211010835.

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To address the problems of the low accuracy of geometric error identification and incomplete identification results of the linear axis detection of computer numerical control (CNC) machine tools, a new 21-item geometric error identification method based on double ball-bar measurement was proposed. The model between the double ball-bar reading and the geometric error term in each plane was obtained according to the three-plane arc trajectory measurement. The mathematical model of geometric error components of CNC machine tools is established, and the error fitting coefficients are solved through the beetle antennae search particle swarm optimization (BAS–PSO) algorithm, in which 21 geometric errors, including roll angle errors, were identified. Experiments were performed to compare the optimization effect of the BAS–PSO and PSO and BAS and genetic particle swarm optimization (GA–PSO) algorithms. Experimental results show that the PSO algorithm is trapped in the local optimum, and the BAS–PSO is superior to the other three algorithms in terms of convergence speed and stability, has higher identification accuracy, has better optimization performance, and is suitable for identifying the geometric error coefficient of CNC machine tools. The accuracy and validity of the identification results are verified by the comparison with the results of the individual geometric errors detected through laser interferometer experiments. The identification accuracy of the double ball-bar is below 2.7 µm. The proposed identification method is inexpensive, has a short processing time, is easy to operate, and possesses a reference value for the identification and compensation of the linear axes of machine tools.

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Mitton, Roger. "Computer-Readable Corpora of Spelling Errors." TESOL Quarterly 21, no. 1 (March 1987): 153. http://dx.doi.org/10.2307/3586361.

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Baumann, R. "Soft Errors in Advanced Computer Systems." IEEE Design and Test of Computers 22, no. 3 (May 2005): 258–66. http://dx.doi.org/10.1109/mdt.2005.69.

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Glauser, Jonathan. "Does Computer Technology Reduce Medical Errors?" Emergency Medicine News 31, no. 5 (May 2009): 5. http://dx.doi.org/10.1097/01.eem.0000351376.14850.fc.

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Wong, P. W. "On quantization errors in computer vision." IEEE Transactions on Pattern Analysis and Machine Intelligence 13, no. 9 (1991): 951–56. http://dx.doi.org/10.1109/34.93812.

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Lang, Kathy L., Arthur C. Graesser, and Darold D. Hemphill. "UNDERSTANDING ERRORS IN HUMAN COMPUTER INTERACTION." ACM SIGCHI Bulletin 23, no. 4 (October 1991): 43–45. http://dx.doi.org/10.1145/126729.1055553.

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Guglin, Maya E., and Deepak Thatai. "Common errors in computer electrocardiogram interpretation." International Journal of Cardiology 106, no. 2 (January 2006): 232–37. http://dx.doi.org/10.1016/j.ijcard.2005.02.007.

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Valenstein, Paul, and Frederick Meier. "Outpatient Order Accuracy." Archives of Pathology & Laboratory Medicine 123, no. 12 (December 1, 1999): 1145–50. http://dx.doi.org/10.5858/1999-123-1145-ooa.

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Abstract Context.—Laboratory test order entry errors potentially delay diagnosis, consume resources, and cause patient inconvenience. Objective.—To evaluate the frequency and causes of computer order entry errors in outpatients. Design.—Cross-sectional survey and prospective sample of errors. Participants answered questions about their test order entry policies and practices. They then examined a sample of outpatient requisitions and compared information on the requisition with information entered into the laboratory computer system. Order entry errors were divided into 4 types: tests ordered on the requisition, but not in the computer; tests performed but not ordered on the requisition; physician name discrepancies; and test priority errors. Participants.—Six hundred sixty laboratories enrolled in the College of American Pathologists Q-Probes program. Main Outcome Measure.—Overall order entry error rate. Results.—A total of 5514 (4.8%) of 114 934 outpatient requisitions were associated with at least 1 order entry error. The median participant reported 1 or more order errors on 6.0% of requisitions; 10% of institutions reported errors with at least 18% of requisitions. Of the 4 specific error types, physician name discrepancies had the highest error rate, and test priority errors the lowest error rate. Four institutional factors were significantly associated with higher overall error rates: orders verbally communicated to the laboratory; no policy requiring laboratory staff to compare a printout or display of ordered tests with the laboratory requisitions to confirm that orders had been entered correctly; failure to monitor the accuracy of outpatient order entry on a regular basis; and a higher percentage of occupied beds (ie, a busier hospital). Conclusions.—Computer order entry errors are common, involving 5% of outpatient requisitions. Laboratories may be able to decrease error rates by regularly monitoring the accuracy of order entry, substituting written and facsimile orders for verbal orders, and instituting a policy in which orders entered into computer systems are routinely rechecked against orders on requisitions.

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Frese, Michael, Felix Brodbeck, Torsten Heinbokel, Christina Mooser, Erik Schleiffenbaum, and Petra Thiemann. "Errors in Training Computer Skills: on the Positive Function of Errors." Human–Computer Interaction 6, no. 1 (March 1991): 77–93. http://dx.doi.org/10.1207/s15327051hci0601_3.

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Wee, Nam-Sook. "Optimal Maintenance Schedules of Computer Software." Probability in the Engineering and Informational Sciences 4, no. 2 (April 1990): 243–55. http://dx.doi.org/10.1017/s026996480000156x.

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We present a decision procedure to determine the optimal maintenance intervals of a computer software throughout its operational phase. Our model accounts for the average cost per each maintenance activity and the damage cost per failure with the future cost discounted. Our decision policy is optimal in the sense that it minimizes the expected total cost. Our model assumes that the total number of errors in the software has a Poisson distribution with known mean λ and each error causes failures independently of other errors at a known constant failure rate. We study the structures of the optimal policy in terms of λ and present efficient numerical algorithms to compute the optimal maintenance time intervals, the optimal total number of maintenances, and the minimal total expected cost throughout the maintenance phase.

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Wu, Xiao Li. "Attention Failure Model in Human-Computer Interactive Interface." Advanced Materials Research 1049-1050 (October 2014): 1885–88. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1885.

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Errors are common human failures occurring in information interface and its cognition mechanism of errors is an important hitting-point for improving interface design as well as the key for reducing cognition difficulties. This paper studies error factors of information interface in human-computer interaction based on visual cognition theory. A feasible attention failure model is established to solve some design problems which result in serious failures in information recognition and analysis, and even in operation and execution processes.

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Ti-Chiun Chang and J. P. Allebach. "Quantization of accumulated diffused errors in error diffusion." IEEE Transactions on Image Processing 14, no. 12 (December 2005): 1960–76. http://dx.doi.org/10.1109/tip.2005.859372.

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Hoang, Trung Kien, and Nguyen Minh Duc Ta. "Machining Based Geometric Error Estimation Method for 3-Axis CNC Machine." Applied Mechanics and Materials 889 (March 2019): 469–74. http://dx.doi.org/10.4028/www.scientific.net/amm.889.469.

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Computer numerical control (CNC) machine tool plays an extremely significant role in any manufacturing industry due to its automation and high accuracy. Keeping the CNC machine tool at its highest performance to meet the demand of high accuracy machining is always significant. To maintain the accuracy of a machine tool over the time, it is important to measure and compensate the geometric error, one of the main error source of machine tool, especially when the machine get old. There are totally 21 geometrical errors in a 3-axis machine tool including three translational errors and three rotational errors for each axis and three perpendicular error (Squareness) within three axes of the machine. This paper presents an economical and simple method for measuring the geometric error of a 3-axis CNC machine tool based on the machining of actual samples. Three samples for each axis will be machined following a design cutting path. The samples will then be measured using a coordinate measuring machine (CMM). The collect data will be used for estimating the geometric errors. The volumetric errors will be then computed and verified through machining of 3D geometries.

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Soergel, David A. W. "Rampant software errors may undermine scientific results." F1000Research 3 (July 29, 2015): 303. http://dx.doi.org/10.12688/f1000research.5930.2.

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The opportunities for both subtle and profound errors in software and data management are boundless, yet they remain surprisingly underappreciated. Here I estimate that any reported scientific result could very well be wrong if data have passed through a computer, and that these errors may remain largely undetected. It is therefore necessary to greatly expand our efforts to validate scientific software and computed results.

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Das, P. K. "Codes on Key Errors." Cybernetics and Information Technologies 14, no. 2 (July 15, 2014): 31–37. http://dx.doi.org/10.2478/cait-2014-0017.

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Abstract Coding theory has started with the intention of detection and correction of errors which have occurred during communication. Different types of errors are produced by different types of communication channels and accordingly codes are developed to deal with them. In 2013 Sharma and Gaur introduced a new kind of an error which will be termed “key error”. This paper obtains the lower and upper bounds on the number of parity-check digits required for linear codes capable for detecting such errors. Illustration of such a code is provided. Codes capable of simultaneous detection and correction of such errors have also been considered.

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Wallis, Alan D. "Considerations of errors in computer‐based measurements." Journal of the Acoustical Society of America 96, no. 5 (November 1994): 3272. http://dx.doi.org/10.1121/1.411358.

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Poole, Alan B., Kelly E. Caine, Arthur D. Fisk, and Wendy A. Rogers. "Errors of Disclosure in Computer Mediated Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 54, no. 5 (September 2010): 512–16. http://dx.doi.org/10.1177/154193121005400504.

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Robertson, Scott P. "Learning from Errors in Computer Text Editing." Proceedings of the Human Factors Society Annual Meeting 29, no. 1 (October 1985): 28–29. http://dx.doi.org/10.1177/154193128502900110.

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Highland, Harold Joseph. "Computer viruses: Media hyperbole, errors and ignorance." Computers & Security 7, no. 5 (October 1988): 442–50. http://dx.doi.org/10.1016/0167-4048(88)90194-0.

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Booth, Paul A. "Errors and theory in human-computer interaction." Acta Psychologica 78, no. 1-3 (December 1991): 69–96. http://dx.doi.org/10.1016/0001-6918(91)90005-k.

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Mir, Y. A., J. R. R. Mayer, and C. Fortin. "Tool path error prediction of a five-axis machine tool with geometric errors." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 216, no. 5 (May 1, 2002): 697–712. http://dx.doi.org/10.1243/0954405021520391.

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Predicting the actual tool path of a machine tool prior to machining a part provides useful data in order to ensure or improve the dimensional accuracy of the part. The actual tool path can be estimated by accounting for the effect of the machine tool geometric error parameters. In computer aided design/computer aided manufacture (CAD/CAM) systems, the nominal tool path [or CL (cutter location) data] is directly generated from the curves and surfaces to be machined and the errors of the machine tool are not considered. In order to take these errors into consideration, they must first be identified and then used in the machine tool forward kinematic model. In this paper a method is presented to identify the geometric errors of machine tools and predict their effect on the tool-tip position. Both the link errors (position-independent geometric error parameters) and the motion errors (position-dependent geometric error parameters) are considered. The nominal and predicted tool paths are compared and an assessment is made of the resulting surfaces with respect to the desired part profile tolerance. A methodology is also suggested to integrate this tool within a CAD/CAPP (computer aided process planning)/CAM environment.

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Gardner, Dianne, and Robert Wood. "Errors, Feedback, Learning and Performance." Australian and New Zealand Journal of Organisational Psychology 2 (August 1, 2009): 30–43. http://dx.doi.org/10.1375/ajop.2.1.30.

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AbstractThe value of feedback about errors when learning a novel computer-based task was explored in two studies. The first study examined the optimal level of information to be provided in feedback about errors. The second study examined whether framing errors positively as opportunities to learn (which encourages error tolerance) or negatively as hindrances to learning (which encourages error avoidance) facilitated learning and performance. Both studies used a computer-based simulation of a management decision-making task. In the first study there were three feedback conditions: outcome feedback alone, outcome feedback plus error signal feedback, and outcome feedback plus corrective feedback. Corrective feedback produced better performance than error signal and outcome feedback but learning did not differ across the three conditions. Corrective feedback also facilitated the use of systematic exploration which was positively associated with performance and learning. Learners' self-efficacy moderated the effects of error feedback: learners with high self-efficacy showed high levels of performance in all conditions but for those with low self-efficacy, detailed corrective feedback was essential for learning. The second study explored the effects of positive vs. negative error framing and corrective vs. signal error feedback in a 2 × 2 design. Positive error framing produced more unsystematic exploration and worse performance than negative error framing. Positive error framing helped those with low self-efficacy but for those with higher self-efficacy it was of more value to frame errors negatively. The implications of the interactions between error framing, error feedback and learner characteristics are discussed along with implications for the study of error management, a positive error framing technique.

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Bruno, Vincenzo, Mauro Badino, Francesco Riccitiello, Gianrico Spagnuolo, and Massimo Amato. "Computer Guided Implantology Accuracy and Complications." Case Reports in Dentistry 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/701421.

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The computer-based method allows the computerized planning of a surgical implantology procedure, using computed tomography (CT) of the maxillary bones and prosthesis. This procedure, however, is not error-free, unless the operator has been well trained and strictly follows the protocol. A 70-year-old woman whom was edentulous asked for a lower jaw implant-supported prosthesis. A computer-guided surgery was planned with an immediate loading according to the NobelGuide technique. However, prior to surgery, new dentures were constructed to adjust the vertical dimension. An interim screwed metal-resin prosthesis was delivered just after the surgery; however, after only two weeks, it was removed because of a complication. Finally, a screwed implant bridge was delivered. The computer guided surgery is a useful procedure when based on an accurate 3D CT-based image data and an implant planning software which minimizes errors.

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He, Huaqing. "A Computer-Aided Analysis on Word Form Errors in College English Writing — A Corpus-based Study." International Journal of Emerging Technologies in Learning (iJET) 11, no. 03 (March 30, 2016): 4. http://dx.doi.org/10.3991/ijet.v11i03.5158.

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Based on contrastive analysis and computer-aided error analysis, this paper uses qualitative and quantitative methods to explore word form errors committed by Chinese non-English majors in their writing, collected in Chinese Learner English Corpus (CLEC). The aim is to offer English learners some help in the methods to improve their English writing proficiency and yield some suggestions on English language teaching. The main findings are as follows: (1) the word form errors account for 29.42% of the total language errors; (2) there is a negative correlation between word form errors and writing quality; (3) there is a significant difference in word form errors committed by college learners of different writing ability. In the end, the reasons for word form errors are analyzed and some pedagogical suggestions are put forward.

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Yasunaga, Kenji. "Error Correction by Structural Simplicity: Correcting Samplable Additive Errors." Computer Journal 62, no. 9 (October 5, 2018): 1265–76. http://dx.doi.org/10.1093/comjnl/bxy100.

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Abstract This paper explores the possibilities and limitations of error correction by the structural simplicity of error mechanisms. Specifically, we consider channel models, called samplable additive channels, in which (i) errors are efficiently sampled without the knowledge of the coding scheme or the transmitted codeword; (ii) the entropy of the error distribution is bounded; and (iii) the number of errors introduced by the channel is unbounded. For the channels, several negative and positive results are provided. Assuming the existence of one-way functions, there are samplable additive errors of entropy nε for ε∈(0,1) that are pseudorandom, and thus not correctable by efficient coding schemes. It is shown that there is an oracle algorithm that induces a samplable distribution over {0,1}n of entropy m=ω(logn) that is not pseudorandom, but is uncorrectable by efficient schemes of rate less than 1−m/n−o(1). The results indicate that restricting error mechanisms to be efficiently samplable and not pseudorandom is insufficient for error correction. As positive results, some conditions are provided under which efficient error correction is possible.

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DuBeshter, Brent, Carolyn J. Walsh, Kim Altobelli, John Loughner, and Cynthia Angel. "Experience With Computerized Chemotherapy Order Entry." Journal of Oncology Practice 2, no. 2 (March 2006): 49–52. http://dx.doi.org/10.1200/jop.2006.2.2.49.

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Purpose The elimination of errors related to chemotherapy administration remains an elusive goal. Computerized order entry has been shown to reduce errors. We assessed a chemotherapy computer order entry system for errors related to dosing and for the time required to prepare chemotherapy orders. Methods A prospective study of all patients treated with chemotherapy over a 12-month period was performed. Chemotherapy order sets done via computerized order entry were reviewed for errors related to drug selection, dose calculations, decimal-point errors, and for exceeding a warning level set within the system. We also measured the time required to produce three order sets by hand versus by computer. Results There were no errors in dose calculations, decimal points, or drug selection for 2,558 drug administrations in 235 patients treated with 26 different chemotherapy regimens. The dose warning level was exceeded in 152 (6%) of drug administrations, but never without user permission to override the warning. The average time saved per order set using computer order entry was 10 minutes (P < .05). Conclusion By using computer order entry with error-checking algorithms, it may be possible to eliminate a number of types of errors associated with chemotherapy administration without sacrificing efficiency.

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Ziegert, J. C., D. G. Olson, and P. Datseris. "Description of Machine Tool Errors Using Screw Coordinates." Journal of Mechanical Design 114, no. 4 (December 1, 1992): 531–35. http://dx.doi.org/10.1115/1.2917039.

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The kinematic behavior of a mechanism may be modeled using a number of different formalisms. In this paper, the description of machine tool errors is examined using screw coordinates. The six components of error associated with each axis motion, three rotational errors about the three coordinate axes and three translational errors of the origin along the coordinate axes, are shown to be identically the six components of an “error twist,” or screw displacement. This “error twist” is a motor, and the six components of the motor are, in general, functions of the axis position. Thus, the “error twist” is a motor valued function of a scalar variable which describes axis errors in an extremely compact form. Furthermore, this approach allows clearer insights into errors which arise due to the Abbe´ effect. Using screw-coordinates to describe the machine errors, it becomes clear that the so-called Abbe´ errors cannot be eliminated in the general case, even if the tool point is collinear with the machine scale. However, the relative importance of these errors can be easily determined since the location of the instantaneous axis of rotation is easily found. Expressions are developed which allow the translational components of the errors to be measured at any convenient points on the body, including differing points for each component, and properly transformed into error motions of any desired point. Finally, a method for determining the total error at the tool point due to the individual error components of each of the members is presented.

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Yao, Ligang, Jian S. Dai, and Guowu Wei. "Error Analysis and Compensation for Meshing Contact of Toroidal Drives." Journal of Mechanical Design 128, no. 3 (July 18, 2005): 610–17. http://dx.doi.org/10.1115/1.2179460.

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This paper investigates the meshing errors of the toroidal drive, reveals three typical latency errors and develops the error analysis in this typical type of gear drives. Having identified the latency errors, the error integrated coordinate transformation is implemented. This leads to the development of the error impinged meshing model. The model reveals for the first time the effect of the latency errors in gear meshing contact of a toroidal drive and characterizes the error effect on meshing contact. The effect of these errors on the gear coordinate frames is hence presented and on the contact paths of rollers is analyzed. The study leads to a new method for compensating the three latency errors by introducing a bearing with a changeable oil film. The method is then verified in a prototype and demonstrates to be effective.

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Can, Cem. "Agreement Errors in Learner Corpora across CEFR: A Computer-Aided Error Analysis of Greek and Turkish EFL Learners Written Productions." Journal of Education and Training Studies 6, no. 5 (March 31, 2018): 77. http://dx.doi.org/10.11114/jets.v6i5.3064.

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This paper illustrates the use of learner corpus data (extracted from Cambridge Learner Corpus – CLC) to carry out an error analysis to investigate authentic learner errors and their respective frequencies in terms of types and tokens as well as contexts in which they regularly occur across four distinct proficiency levels, B1-B2; C1-C2, as defined by Common European Framework of Reference for Languages (henceforth CEFR) (Council of Europe, 2001). As a variety of learner corpora compiled by researchers become relatively accessible, it is possible to explore interlanguage errors and conduct error analysis (EA) on learner-generated texts. The necessity to cogitate over these authentic learner errors in designing foreign language learning programs and remedial teaching materials has been widely emphasized by many researchers (see e.g., Juozulynas, 1994; Mitton, 1996; Cowan, Choi, & Kim, 2003; Ndiaye & Vandeventer Faltin, 2003; Allerton et al., 2004). This study aims at conducting a corpus-based error analysis of agreement errors to reveal the related error categories between Greek and Turkish EFL learners, the distribution of agreement errors along the B1 - C2 proficiency range according to CEFR, and the distribution of agreement error types in respect of the L1 of the learners. The data analyzed in this study is extracted from the Cambridge Learner Corpus (CLC), the largest annotated test performance corpus which enables the investigation of the linguistic and rhetorical features of the learner performances in the above stated proficiency bands. The findings from this study reveal that, across B1-C2 proficiency levels and across different registers and genres, the most common agreement error categories by the frequency in which they occur are Verb Agreement (AGV), Noun Agreement (AGN), Anaphor Agreement (AGA), Determiner Agreement (AGD), Agreement Error (AG), and Quantifier Agreement (AGQ) errors. This study’s approach uses the techniques of computer corpus linguistics and follows the steps of the Error Analysis framework proposed by Corder (1971): identification, description, classification and explanation of errors.

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Cohen, Michael R. "Ephedrine–Epinephrine Mix-Ups Nurse Computer Order Entry Leads to Error Precisely Wrong." Hospital Pharmacy 38, no. 7 (July 2003): 629–31. http://dx.doi.org/10.1177/001857870303800708.

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These medication errors have occurred in health care facilities at least once. They will happen again—perhaps where you work. Through education and alertness of personnel and procedural safeguards, they can be avoided. You should consider publishing accounts of errors in your newsletters and/or presenting them in your inservice training programs. Your assistance is required to continue this feature. The reports described here were received through the USP Medication Errors Reporting Program, which is presented in cooperation with the Institute for Safe Medication Practices. If you have encountered medication errors and would like to report them, you may call USP toll-free, 24 hours a day, at 800–233–7767 (800–23-ERROR). Any reports published by ISMP will be anonymous. Comments are also invited; the writers‘ names will be published if desired. ISMP may be contacted at the address shown below.

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Shneiderman, Ben. "Tragic errors." Interactions 18, no. 6 (November 2011): 60–63. http://dx.doi.org/10.1145/2029976.2029992.

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Ravichandran, Jamuna, and Natarajan Uthirapathy. "Measurement of error in computer numerical control machines and optimization using teaching–learning-based optimization algorithm." Measurement and Control 52, no. 7-8 (May 13, 2019): 929–37. http://dx.doi.org/10.1177/0020294019847699.

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The accuracy of computer numerical control machine tools can be improved by identifying error sources affecting the overall position error and orientation errors. Because of their inevitable nature, the position errors cannot be entirely eliminated from the machinery, but they can be identified, measured and compensated during the manufacturing process of the components by developing and using a mathematical model. In this present work, different mathematical models have been developed for the errors measured by laser interferometer at different nominal positions of X, Y and Z axes both in forward and reverse direction movement as per VDI 3441 Germany standard. Using Akaike information criterion, the best model is selected for each axis and later the best model’s coefficients have been optimized by considering both minimizing sum square errors and maximizing R2 values using teaching–learning-based optimization algorithm. Technique for Order Preference by Similarity to the Ideal Solution method has been adopted to convert the dual objectives into a single objective. An improvement of 1%–71% in R2 values was reported to prove the effectiveness of the proposed optimization algorithm, Teaching–Learning-Based Optimization algorithm, with the same sum square error values.

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Smith, J. D. "Practical Rotary Encoder Accuracy Limits for Transmission Error Measurement." Proceedings of the Institution of Mechanical Engineers, Part C: Mechanical Engineering Science 205, no. 6 (November 1991): 431–36. http://dx.doi.org/10.1243/pime_proc_1991_205_141_02.

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Errors of angular position on encoders used for transmission error measurement were investigated to determine the practical limits of accuracy. Computer correction can be used to eliminate consistent errors on the encoders but errors remain, attributable to electrical noise, bearing errors and friction effects. Practical limits on the calibration and usage of the encoders for individual harmonics of once per revolution frequency and for a given angular position were established.

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Zhang, Zhimin. "High-Speed Serial Data Transmission Error Control Based on Fuzzy Classification." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 7 (November 20, 2018): 1077–81. http://dx.doi.org/10.20965/jaciii.2018.p1077.

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At present, the error control method for high-speed serial data transmission obtains the errors by comparison and then controls them. If the data transmission channel is not denoised, the packet loss and error codes become serious, and energy consumption increases. The use of fuzzy classification is proposed to control data transmission errors. The method uses the combination of wavelet transform and transform domain difference to double denoise the channel, and it completes the clustering of data transmission errors by fuzzy classification. Considering packet loss, error codes, and energy consumption in data transmission error control, when the communication distance between two nodes is small, automatic repeat request is used to control data transmission errors. As the distance between nodes increases, forward error correction is used to control data transmission errors. When the communication distance gradually increases, data transmission errors are controlled by hybrid automatic repeat request. Experiments showed that the proposed method can reduce the data transmission error, control energy consumption, packet loss rate, and bit error rate, and enhance the denoising effect.

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JÓŹWIAK, Ireneusz J., and Jakub LEGUT. "Strategies of tolerating errors in computer system working." Scientific Papers of Silesian University of Technology. Organization and Management Series 2018, no. 130 (2018): 269–76. http://dx.doi.org/10.29119/1641-3466.2018.130.24.

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Santell, John P., Joanne G. Kowiatek, Robert J. Weber, Rodney W. Hicks, and Carl A. Sirio. "Medication errors resulting from computer entry by nonprescribers." American Journal of Health-System Pharmacy 66, no. 9 (May 1, 2009): 843–53. http://dx.doi.org/10.2146/ajhp080208.

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Journal articles on the topic 'Computer errors'

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