Relevant bibliographies by topics / Error Analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Error Analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Error Analysis"

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Berninger, Virginia W., and Barbara Alsdorf. "Are there Errors in Error Analysis?" Journal of Psychoeducational Assessment 7, no. 3 (September 1989): 209–22. http://dx.doi.org/10.1177/073428298900700303.

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Lestari, Widi, Setia Muljanto, and Lusiana Lestari. "GRAMMATICAL ERROR ANALYSIS IN EFL SPEAKING PERFORMANCE." English Education and Applied Linguistics Journal (EEAL Journal) 3, no. 2 (August 3, 2020): 124–28. http://dx.doi.org/10.31980/eealjournal.v3i2.1840.

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This study was carried out to analyze the grammatical errror analysis which are made by the students in their speaking performance. It was based on the assumption that grammatical rule has a function in speaking to make the communication clearly and to convey the information in appropriate way. The study was conducted under qualitative methodology by using case study as the appropriate research design. The data source of this research is 1st grade student from the speaking class of English Education major that consisted of 24 students. For collecting the data, the researcher used observation fieldnote and also video record. The writer identified and analyzed data based on the types of error using Dulay’s theory. Based on the finding, the result of this research showed that students made a total errors 318 times divided into four types of errors: omission, addition, misformation, and misordering. From the quantity of each error types, misformation was the highest errors produced by the students. It took 175 times of errors. And omission had 115 times of errors, moreover, 24 errors fell into error of addition, and the last one misordering was the lowest errors produced by the students the total was 5 errors. Actually, errors are necessary in learning a language, especially learning English language as the foreign language. Thus, error analysis also helps the students identify what the errors are made, because the students cannot apply their language acquisition directly without committing error firstly. They cannot achieve the target language perfectly when the errors appear. Error analysis is very advantageous for both learner and teacher. For learner, by paying more attention, the learners are expected to increase their knowledge on the English grammar. Whereas for teachers, hopefully the research can be useful information in teaching process and in the end, the teacher can be able to teach the material appropriately
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Nurlaeli, Prita Dwi, and Arif Widiyatmoko. "ANALYSIS OF STUDENTS’ ERRORS WITH NEWMAN'S ERROR ANALYSIS ON VIBRATION, WAVES AND SOUNDS CONCEPT." Jurnal Pendidikan Matematika dan IPA 14, no. 1 (January 10, 2023): 43. http://dx.doi.org/10.26418/jpmipa.v14i1.52312.

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This study aims to find out what errors were made by Class VIII Junior High School students in story problem solving vibration, wave, and sound based on Newman's Error Analysis (NEA). And find out what factors are the cause of the error. This research is a qualitative research with a descriptive aroach. The data collection technique used is by using written tests, interviews, observations, and documentation. Then analyze the data using data reduction, data presentation, and verification. The results of this study indicated that Newman's Error Analysis can find out what mistakes were made by students and how these errors could occur. As for question number one, the percentage of reading errors is 0%, comprehension error is 14.28%, transformation error is 28.57%, process skills error is 19.04%, and encoding error is 0%. For question number two, the percentage of reading errors is 0%, comprehension error is 14.28%, transformation error is 19.04%, process skills error is 28.57%, and encoding error is 0%. Question number three type of reading error is 4.76%, comprehension error is 23.80%, transformation error is 9.52%, process skills error is 23.80%, and encoding error is 0%. Question number four reading error 0%, comprehension error 33.33% transformation error 19.04%, process skills error and encoding error is 0%. Question number five obtained 0% reading error, 33.33% comprehension error, 4.76% transformation and process skills, and 0% encoding error. This study concludes that many students experience errors because students don't understand the concept of the problem and are less thorough in working on the problem. From this it could be used as an evaluation for both students and teachers to be improving the learning process to make it more effective.
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Moriyanti, Moriyanti, and Nyak Mutia Ismail. "Communicative Effect Taxonomy Analysis in Students� Oral Production." English LAnguage Study and TEaching 4, no. 2 (January 15, 2024): 47–62. http://dx.doi.org/10.32672/elaste.v4i2.7338.

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This study aims at finding out Communicative Effect Taxonomy in students oral productionspecifically on local and global errors. This study is qualitative in nature involving 16 first grader at SMPN 2 Muara Tiga, Pidie. The instrument used was analytical table which was constructed based on the theory of Communicative Effect Taxonomy. The data collection was carried out by following the steps of: sample collection, errors identification, error description, error clarification, and error assessment. The data analysis was conducted afterward in line with the following phases: identification of errors, classification of errors, evaluation, and conclusion. It is found that local erros were produced more compared to global errors (52 local errors and 45 global errors) in the students speaking performance. Regarding the implication, the result from this study can enhance the development of more accurate and dependable evaluation tools for measuring students' oral communication skills by establishing a classification system for communicative impacts. Consequently, this can exert a substantial influence on educational policies and practices.
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McCloskey, George. "Error Analysis." Journal of Psychoeducational Assessment 35, no. 1-2 (September 26, 2016): 242–50. http://dx.doi.org/10.1177/0734282916669911.

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This commentary will take an historical perspective on the Kaufman Test of Educational Achievement (KTEA) error analysis, discussing where it started, where it is today, and where it may be headed in the future. In addition, the commentary will compare and contrast the KTEA error analysis procedures that are rooted in psychometric methodology and the process approach to error analysis which is derived primarily from cognitive neuropsychology.
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Raabe, Horst. "Error analysis." System 21, no. 3 (August 1993): 394–96. http://dx.doi.org/10.1016/0346-251x(93)90030-k.

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Vidhiasi, Dhion Meitreya, and Haryani Haryani. "The Implementation of Grammarly In Error Analysis Implementasi Grammarly Dalam Error Analysis." JURNAL SAINS DAN TEKNOLOGI MARITIM 21, no. 1 (October 15, 2020): 17. http://dx.doi.org/10.33556/jstm.v21i1.248.

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<p>English is still considered as a difficult thing to learn, both for students and teachers. That is because English is still regarded as a foreign language and is rarely used in daily conversation. The difficulty in mastering English is found not only in the speaking aspect but also in the writing element. In examining student writing (error analysis), lecturers at the Akademi Maritim Nusantara Cilacap used a program called Grammarly. This study aims to see the implementation of Grammarly in helping lecturers make Error Analysis. Researchers found that Grammarly was enough to help lecturers in conducting error analysis. Researchers then classify the types of errors found in student writing using Grammarly. From 7 (seven) student writings that were used as data sources in this study, there were 9 (nine) types of errors that were made in the writing of the seven students. The most common errors were errors with spelling (39%) and punctuation (40.3%). Although Grammarly is proven to help the work of lecturers in conducting Error Analysis, Grammarly still cannot find sentences that have errors semantically quickly.</p><p><strong> </strong></p>
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Winarso, Widodo, Sirojudin Wahid, and Rizkiah Rizkiah. "TYPE OF ERROR IN COMPLETING MATHEMATICAL PROBLEM BASED ON NEWMAN’S ERROR ANALYSIS (NEA) AND POLYA THEORY." Jurnal Pendidikan Matematika dan IPA 13, no. 1 (January 25, 2022): 51. http://dx.doi.org/10.26418/jpmipa.v13i1.44765.

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This study disscusses student’s errors in completing mathematical problems based on Newman’s Errror Analysis and Polya Theory. The study uses a qualitative descriptive approach. The subject of this study are 78 students of Madrasah Aliyah Negeri (MAN) 2 Cirebon. The study uses tests and interviews as data collection techniques. Students take a test to determine their mathematical ability, and the test uses sequence and series as subjects. There are 3 phases in collecting data: data reduction, data presentation, and conclusion. Outline of Error analysis is created using five types of student mathematical error of Newman's Error Analysis and four types of student mathematical error of Polya Theory. The study results based on Newman's Error Analysis are errors reading by 1%, error understanding by 0%, error transforms by 3%, error processing ability by 5%, and error encoding by 7%. As the result of the study based Polya theory, errors when understanding the problem by 31%, errors when devising a plan by 11%, errors when carrying out the plan by 9%, and errors when Looking back by 33%. The result of the interview shows that the error occurs when students don’t do calculations carefully, don’t learn the formula, and cannot distinguish between sequence and series. Students also have a lack of understanding when completing the problem about compound interest.
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Liu, Yang, and Jianguo Tian. "Error Analysis of College Students’ Spoken English." International Journal of Languages, Literature and Linguistics 7, no. 4 (December 2021): 182–88. http://dx.doi.org/10.18178/ijlll.2021.7.4.309.

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Based on the theory of Error Analysis, this thesis records the production of spoken English of first year college students of Northwestern Polytechnical University as samples. After listening to the recorder repeatedly and carefully, the author classifies and describes the errors found in the corpus, investigates the causes of these errors and provides solutions to these problems. It is found that there are errors of performance, phonological errors, lexical errors, grammatical errors and pragmatic errors in this study. Reasons for these errors can be explained from the perspectives of interlingual transfer, intralingual interference, cognitive and affective factors, and communicative strategies. Accordingly, some countermeasures could be taken to effectively decrease errors.
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Sun, Chunhua, Ichiro Hagiwara, and Zhuoqi Wu. "1318 Error Analysis for Parameterizing Triangular Meshes." Proceedings of Design & Systems Conference 2005.15 (2005): 152–53. http://dx.doi.org/10.1299/jsmedsd.2005.15.152.

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Dissertations / Theses on the topic "Error Analysis"

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Recski, Leonardo Juliano. "Computer-assisted error analysis." Florianópolis, SC, 2002. http://repositorio.ufsc.br/xmlui/handle/123456789/83383.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Comunicação e Expressão.
Made available in DSpace on 2012-10-19T23:29:05Z (GMT). No. of bitstreams: 0Bitstream added on 2014-09-26T01:57:45Z : No. of bitstreams: 1 181888.pdf: 3989754 bytes, checksum: faa45dc1485896a97588e233b76a1a61 (MD5)
Programas para, a análise de texto para microcomputadores já estão disponíveis há algum tempo. A técnica de análise de erros preposicionais auxiliada por computador, um novo
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Ozores, Ana Luiza Festa. "Entendendo alguns erros do Ensino Fundamental II que os alunos mantêm ao final do Ensino Médio." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/45/45135/tde-28102017-073627/.

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É natural considerar o erro como algo que deve ser evitado, um indicador de mau desempenho. Desde pequenas, as crianças são habituadas a buscar os acertos, de forma que, quando o raciocínio está errado, elas devem refazê-lo. Tal resultado é cobrado em casa pela família e na escola pelos educadores. Porém, o erro é o mais antigo elemento no processo de aprendizagem, e, além de ser um indicador de desempenho, o erro também mostra aquilo que o aluno sabe ou pensa ter compreendido. É possível notar que alguns alunos do Ensino Médio mantêm erros e dúvidas que deveriam ter sido sanados ao longo do Ensino Fundamental. Neste trabalho, será analisado o porquê de essas dúvidas ainda se apresentarem, pois a análise desses erros pode auxiliar tanto o aluno como o professor. O aluno, com uma devolutiva do que foi feito para tentar aprimorar o seu saber e o professor, levando-o a elaborar novas estratégias didáticas e planos de ensino que melhor se adaptem ao seu público alvo.
It is expected to consider the error as something that must be avoided, a non-satisfactory performance indicator. Since childhood, the human being is used to seek the right answers, so that, when the reasoning is wrong, he/she should remake it. Such outcome is charged at home by the family and at school by the teachers. However, the error is the oldest element in the learning process and, in addition to being a performance indicator, the error also shows something that the student knows or thinks he/she has understood. It is possible to notice that some high school students make some mistakes or has some doubts that were supposed to be clarified during the elementary school. In this paper, it will be analyzed the reason why these doubts are still present, because the analysis of these errors can help both students and teachers. The students, with a feedback of what has been done to try to improve their knowledge and the teacher, leading him to design new teaching strategies and lesson plans to best suit his/her target audience.
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Attwal, Preet Singh. "Objective error measure techniques for error analysis and control within the finite element analysis process." Thesis, Cranfield University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340874.

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Lo, Sau Yee. "Measurement error in logistic regression model /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?MATH%202004%20LO.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.
Includes bibliographical references (leaves 82-83). Also available in electronic version. Access restricted to campus users.
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Masani, Deekshitha. "Analysis of radiation induced errors in transistors in memory elements." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/theses/2791.

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From the first integrated circuit which has 16-transistor chip built by Heiman and Steven Hofstein in 1962 to the latest 39.54 billion MOSFET’s using 7nm FinFET technology as of 2019 the scaling of transistors is still challenging. The scaling always needs to satisfy the minimal power constraint, minimal area constraint and high speed as possible. As of 2020, the worlds smallest transistor is 1nm long build by a team at Lawrence Berkeley National Laboratory. Looking at the latest trends of 14nm, 7nm technologies present where a single die holds more than a billion transistors on it. Thinking of it, it is more challenging for dyeing a 1nm technology. The scaling keeps going on and if silicon does not satisfy the requirement, they switch to carbon nanotubes and molybdenum disulfide or some newer materials. The transistor sizing is reducing but the pressure of radiation effects on transistor is in quench of more and more efficient circuits to tolerate errors. The radiation errors which are of higher voltage are capable of hitting a node and flipping its value. However, it is not possible to have a perfect material to satisfy no error requirement for a circuit. But it is possible to maintain the value before causing the error and retain the value even after occurrence of the error. In the advanced technologies due to transistor scaling multiple simultaneous radiation induced errors are the issue. Different latch designs are proposed to fix this problem. Using the CMOS 90nm technology different latch designs are proposed which will recover the value even after the error strikes the latch. Initially the errors are generally Single event upsets (SEUs) which when the high radiation particle strikes only one transistor. Since the era of scaling, the multiple simultaneous radiation errors are common. The general errors are Double Node Upset (DNU) which occurs when the high radiation particle strikes the two transistors due to replacing one transistor by more than one after scaling. Existing designs of SEUs and DNUs accurately determine the error rates in a circuit. However, with reference to the dissertation of Dr. Adam Watkins, proposed HRDNUT latch in the paper “Analysis and mitigation of multiple radiation induced errors in modern circuits”, the circuits can retain its error value in 2.13ps. Two circuits are introduced to increase the speed in retaining the error value after the high energy particle strikes the node. Upon the evaluation of the past designs how the error is introduced inside the circuit is not clear. Some designs used a pass gate to actually introduce the error logic value but not in terms of voltage. The current thesis introduces a method to introduce error with reduced power and delay overhead compared to the previous circuits. Introducing the error in the circuits from the literature survey and comparing the delay and power with and without introducing the error is shown. Introducing the errors in the two new circuits are also shown and compared with when no errors are injected.
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Tang, Stanley C. "Robot positioning error analysis and correction." Thesis, This resource online, 1987. http://scholar.lib.vt.edu/theses/available/etd-04122010-083623/.

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Juretic, Franjo. "Error analysis in finite volume CFD." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420616.

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Miguel, Angela Ruth. "Human error analysis for collaborative work." Thesis, University of York, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.441020.

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Bonnot, Justine. "Error Analysis for Approximate Computing Systems." Thesis, Rennes, INSA, 2019. https://partages.insa-rennes.fr/alfresco/s/api/node/content/workspace/SpacesStore/4b8b3149-5fc4-439b-abc5-ef663a070daf/2019ISAR0008_BONNOT_Justine.pdf?a=true.

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Le calcul approximé est une technique de calcul efficace en énergie et reposant sur l'exploitation de la tolérance à l'imprécision d'une application. Développé pour faire face à la fin de la loi de Moore, il répond à une demande croissante en capacité de calcul. Les techniques d'approximation ont été proposées à différents niveaux d'abstraction, du circuit au système. Cette thèse porte sur le développement de méthodes et outils permettant d'évaluer rapidement l'impact des différentes techniques d’approximation sur la qualité du résultat en sortie d'une application. L'étude des erreurs induites est essentielle pour utiliser ces approximations dans l'industrie. Deux niveaux d’approximation ont été considérés, le niveau matériel avec l'étude des opérateurs arithmétiques inexacts et le niveau des données avec l'étude de l'arithmétique virgule fixe. Premièrement, des méthodes efficaces de caractérisation basées simulation ont été proposées pour obtenir des statistiques sur les erreurs induites par l'approximation considérée. Les statistiques inférentielles ont été utilisées pour quantifier le nombre d’observations nécessaires pour estimer le statistiques de l’erreur et ainsi réduire le temps d’évaluation. Les méthodes de caractérisation proposées sont basées sur des simulations adaptatives et caractérisent l'erreur d'approximation de façon statistique selon les exigences de confiance définies par l'utilisateur. Ensuite, les métriques d'erreur obtenues ont été reliées à la métrique de qualité de l'application. Pour les opérateurs inexacts, un simulateur a été conçu pour le processus d’exploration de l’espace d’approximation pour sélectionner la meilleure pour l’application considérée. Pour la virgule fixe, le modèle d’erreur a été intégré à un algorithme de raffinage pour déterminer la largeur optimisée des variables de l’application. Les résultats de cette thèse proposent des méthodes concrètes pour faciliter la mise en œuvre du calcul approximé dans les applications industrielles, accélérant les méthodes proposées dans l’état de l’art de un à trois ordres de grandeur
Approximate Computing is an energy- aware computing technique that relies on the exploitation of the tolerance to imprecision of an application. Developed to face the end of Moore’s law, it answers the growing demand in computing capacity. Approximation techniques have been proposed at different abstraction levels, from circuit to system level. This thesis focuses on the development of methods and tools to quickly evaluate the impact of different Approximate Computing techniques on the application quality metric. The study of the induced errors is critical to use approximations in the industry. Approximate Computing techniques have been considered at two different levels, the hardware level with the study of inexact arithmetic operators and the data level with the study of fixed-point arithmetic. First, efficient simulation-based characterization methods have been proposed to derive statistics on the errors induced by the considered approximation. Inferential statistics have been proposed to reduce the time for error characterization. The proposed characterization methods are based on adaptive simulations and statistically characterizes the approximation error according to user-defined confidence requirements. Then, the obtained error metrics are linked with the application quality metric. For inexact operators, a simulator has been proposed for the approximation design space exploration process to select the best approximation for the considered application. For fixed-point arithmetic, the proposed error model has been implemented in a fixed-point refinement algorithm to determine the optimized word-lengths of the internal variables in an application. The results of this thesis are proposing concrete methods to ease the implementation of Approximate Computing in industrial applications, speeding up state-of-the-art methods from one to three orders of magnitude
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Hirst, William Mark. "Outcome measurement error in survival analysis." Thesis, University of Liverpool, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366352.

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Books on the topic "Error Analysis"

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Peng, Wendy W. Software error analysis. Summit, N.J: Silicon Press, 1995.

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Peng, Wendy W. Software error analysis. Gaithersburg, MD: U.S. Dept. of Commerce, National Institute of Standards and Technology, 1993.

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Ḥusaynī, Muḥammad Z̤iyāʼ. Questions and answers on contrastive analysis & error analysis. Tihrān: Intishārāt-i Rahnamā, 2006.

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L, Chiappetta, Gosman A. D, and United States. National Aeronautics and Space Administration., eds. Error reduction program: Final report. [Washington, DC]: National Aeronautics and Space Administration, 1985.

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United States. National Aeronautics and Space Administration., ed. Error modeling for differential GPS. Cambridge, Mass: Charles Stark Draper Laboratory Inc., 1995.

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Kotulski, Zbigniew A., and Wojciech Szczepinski. Error Analysis with Applications in Engineering. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3570-7.

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Biemer, Paul P. Latent Class Analysis of Survey Error. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470891155.

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Kotulski, Zbigniew. Error analysis with applications in engineering. Dordrecht: Springer, 2010.

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aut, Valero Garcés Carmen, ed. Learning to write: Error analysis applied. Alcala de Henares, Madrid: Universidad de Alcalá, 2003.

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Szczepiński, Wojciech. Error analysis with applications in engineering. Rochester, NY: Lastran Corporation, 2000.

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Book chapters on the topic "Error Analysis"

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Schiefer, Hartmut, and Felix Schiefer. "Error Analysis (Error Calculation)." In Statistics for Engineers, 51–68. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-32397-4_4.

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Challis, John H. "Error Analysis." In Experimental Methods in Biomechanics, 197–210. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52256-8_11.

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Stoer, J., and R. Bulirsch. "Error Analysis." In Introduction to Numerical Analysis, 1–36. New York, NY: Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4757-2272-7_1.

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Scherer, Philipp O. J. "Error Analysis." In Graduate Texts in Physics, 3–16. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61088-7_1.

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Kaloyerou, Panayiotis Nicos. "Error Analysis." In Basic Concepts of Data and Error Analysis, 27–59. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95876-7_3.

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Luo, Zhiquan, and Jos Sturm. "Error Analysis." In International Series in Operations Research & Management Science, 163–89. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4381-7_7.

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Gass, Saul I., and Carl M. Harris. "Error analysis." In Encyclopedia of Operations Research and Management Science, 261. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_300.

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Müller, Siegfried. "Error Analysis." In Adaptive Multiscale Schemes for Conservation Laws, 89–111. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-18164-1_5.

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Scherer, Philipp O. J. "Error Analysis." In Computational Physics, 3–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13990-1_1.

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Stoer, J., and R. Bulirsch. "Error Analysis." In Introduction to Numerical Analysis, 1–36. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-21738-3_1.

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Conference papers on the topic "Error Analysis"

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Morrow, Daniel G., Alfred Lee, and Michelle Rodvold. "Analysis of Routine Pilot-Controller Communication." In Human Error Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1990. http://dx.doi.org/10.4271/902352.

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Cardew-Hall, Michael J., and Phillip Dench. "CAD Based Inspection Analysis and Error Display." In ASME 1994 International Computers in Engineering Conference and Exhibition and the ASME 1994 8th Annual Database Symposium collocated with the ASME 1994 Design Technical Conferences. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/cie1994-0435.

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Abstract Modem inspection devices generate large quantites for error data for analysis. This paper describes a CAD based inspection analysis system that utilizes this data. Such a system is requires 1) the definition of error types, 2) the incorporation of tolerances into CAD definitions, 3) generation of errors between actual and nominal CAD geometry, 4) datuming of the geometries, 5) analysis of the errors and 6) display of those errors. The first 4 points are reviewed and a system for analysing and displaying the errors described. Such a system for aerofoil type geometry has been implemented within the CADDS4X CAD system and is described.
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Lee, Jaekwang, Intaik Park, and Edward J. McCluskey. "Error Sequence Analysis." In 26th IEEE VLSI Test Symposium (vts 2008). IEEE, 2008. http://dx.doi.org/10.1109/vts.2008.45.

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Cady, Fredrick M., Donald R. Bjork, Jeffrey Rifkin, and John C. Stover. "BRDF Error Analysis." In 33rd Annual Techincal Symposium, edited by John C. Stover. SPIE, 1990. http://dx.doi.org/10.1117/12.962845.

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Akbari, Muhammad Yudo Agresi. "Arabic Error Analysis." In 1st International Conference on Intellectuals' Global Responsibility (ICIGR 2017). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icigr-17.2018.41.

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Daran, Murial, and Pascale Thévenod-Fosse. "Software error analysis." In the 1996 international symposium. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/229000.226313.

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Khodaygan, S., M. R. Movahhedy, A. Mirabolghasemi, M. Zendehbad, and H. Moradi. "Statistical Error Analysis for Dimensional Control in Automotive Body Assembly Process." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25411.

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In mechanical assemblies, the performance, quality, cost and assemblability of the product are significantly affected by the geometric errors of the parts. This paper develops the statistical error analysis approach for dimensional control in automotive body multi-station assembly process. In this method, the homogeneous transformation matrices are used to describe the location and orientation of part and assembly features and the small homogeneous transformation matrices are used to model the errors. In this approach, the effective errors in automotive body assembly process are classified in three categories: manufacturing errors (dimensional and geometric tolerances), locating errors (fixture errors) and process errors (joining errors). In a mechanical assembly, small variations due the errors propagate according to a complex mechanism that in this approach it formulated in error analysis procedure. The propagation chain of geometric errors is described based on CAD models. The estimation of the error accumulation and the percent contributions of individual errors are based on the statistical model (root-sum-square method). The application of the proposed method is illustrated through presenting an example problem.
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Li, Cong, Yu Zhang, Jialei Wang, Hang Chen, Xian Liu, Tai Huang, Liang Peng, Shen Zhou, Lixin Wang, and Shijian Ge. "From Correctable Memory Errors to Uncorrectable Memory Errors: What Error Bits Tell." In SC22: International Conference for High Performance Computing, Networking, Storage and Analysis. IEEE, 2022. http://dx.doi.org/10.1109/sc41404.2022.00081.

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9

Mei, Jiangping, Yi Li, and Ce Zhang. "The Error Modeling and Accuracy Synthesis of a 3-DOF Parallel Robot Delta-S." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59331.

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The error modeling and precision synthesis of a 3-DOF translational parallel robot named Delta-S are presented. An error model of the system is achieved, ready for precision synthesis. The un-compensable pose error and the compensable pose error are classified according to the error modeling. Based on precision synthesis, the error-coefficient system was built. It indicated the relation between source errors and end errors. An example was taken to demonstrate how to finish above studies. The result shows that the error modeling and the precision-synthesis method have good performance. The work is available for all parallel robots with similar mechanism.
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Cagney, J. L., and S. S. Rao. "Analysis and Synthesis of Mechanical Error in Universal Joints." In ASME 1990 Design Technical Conferences. American Society of Mechanical Engineers, 1990. http://dx.doi.org/10.1115/detc1990-0090.

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Abstract The modeling of manufacturing errors in mechanisms is a significant task to validate practical designs. The use of probability distributions for errors can simulate manufacturing variations and real world operations. This paper presents the mechanical error analysis of universal joint drivelines. Each error is simulated using a probability distribution, i.e., a design of the mechanism is created by assigning random values to the errors. Each design is then evaluated by comparing the output error with a limiting value and the reliability of the universal joint is estimated. For this, the design is considered a failure whenever the output error exceeds the specified limit. In addition, the problem of synthesis, which involves the allocation of tolerances (errors) for minimum manufacturing cost without violating a specified accuracy requirement of the output, is also considered. Three probability distributions — normal, Weibull and beta distributions — were used to simulate the random values of the errors. The similarity of the results given by the three distributions suggests that the use of normal distribution would be acceptable for modeling the tolerances in most cases.
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Reports on the topic "Error Analysis"

1

Peng, Wendy W., and Dolores R. Wallace. Software error analysis. Gaithersburg, MD: National Institute of Standards and Technology, 1993. http://dx.doi.org/10.6028/nist.sp.500-209.

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Anderson, Dylan Zachary, Julia M. Craven, and Steven R. Vigil. SPE-5 Lidar Error Analysis. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1367489.

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Mason, John Jeffrey. TOA/FOA geolocation error analysis. Office of Scientific and Technical Information (OSTI), August 2008. http://dx.doi.org/10.2172/957215.

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Kramer, Steve, and Vinita J. Ghosh. Linac B1 Mis-steering Error Analysis. Office of Scientific and Technical Information (OSTI), November 2013. http://dx.doi.org/10.2172/1505123.

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Wei, J., V. Ptitsin, N. Gelfand, and T. Sen. KEK MQX Field Error Analysis and Compensation. Office of Scientific and Technical Information (OSTI), December 1998. http://dx.doi.org/10.2172/1119555.

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Ptitsin, V., S. Tepikian, and J. Wei. BNL-Built LHC Magnet Error Impact Analysis. Office of Scientific and Technical Information (OSTI), June 1999. http://dx.doi.org/10.2172/1119563.

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Cooper, S. E., A. M. Ramey-Smith, J. Wreathall, and G. W. Parry. A technique for human error analysis (ATHEANA). Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/249298.

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Bunn, M. I., T. R. Carter, H. A. J. Russell, and C. E. Logan. A semiquantitative representation of uncertainty for the 3D Paleozoic bedrock model of Southern Ontario. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331658.

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The southern Ontario bedrock model is a valuable resource for researchers and practitioners, but its application is subject to uncertainty. To address this issue a semi-quantitative approach to visualize the relative effects of data sparsity for each layer, identify regions where a lack of data support reduces model confidence, and quantify potential errors in data collection and model construction is presented. This analysis summarizes several sources of error, including cartesian position error, error in the vertical position of the formation contact, error between the modelled topographic surface and recorded collar elevations, and error between the modelled formation top surface and formation top picks. Where data is present, these errors are added to provide an approximation of total uncertainty. Where data are not present, uncertainty is approximated as 50% of the range in formation top variation, with an average value of 27.5 m across all layers. The results show that data availability strongly influences the average total error for each layer, with deeper layers exhibiting higher total error due to lower data density. However, this analysis also suggests that the modelled surfaces likely carry errors of less than 5 to 10 m in most regions.
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Alasfour, Aisha. Grammatical Errors by Arabic ESL Students: An Investigation of L1 Transfer through Error Analysis. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6436.

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Hunt, Brian D., Aubrey Celia Eckert-Gallup, Lainy Dromgoole Cochran, Terrence D. Kraus, Mark B. Allen, Sean Donovan Fournier, Colin Okada, and Matthew Simpson. Error Analysis of CM Data Products Input Distributions. Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1365477.

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