Relevant bibliographies by topics / Engineering - Statistical methods

Contents

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

Academic literature on the topic 'Engineering - Statistical methods'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Engineering - Statistical methods"

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Marco-Almagro, Lluís, and Xavier Tort-Martorell. "Statistical Methods in Kansei Engineering: a Case of Statistical Engineering." Quality and Reliability Engineering International 28, no. 5 (July 2012): 563–73. http://dx.doi.org/10.1002/qre.1434.

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Abate, Marcey. "Statistical Methods in Software Engineering." Technometrics 43, no. 1 (February 2001): 108. http://dx.doi.org/10.1198/tech.2001.s563.

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Chernick, Michael R., and John E. Brown. "Statistical Methods in Engineering and Manufacturing." Technometrics 33, no. 3 (August 1991): 356. http://dx.doi.org/10.2307/1268787.

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Chernick, Michael R. "Statistical Methods in Engineering and Manufacturing." Technometrics 33, no. 3 (August 1991): 355–56. http://dx.doi.org/10.1080/00401706.1991.10484841.

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Nelson, Lloyd S. "Handbook of Statistical Methods in Engineering." Journal of Quality Technology 25, no. 1 (January 1993): 64–65. http://dx.doi.org/10.1080/00224065.1993.11979420.

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Nelson, Lloyd S. "Statistical Methods in Engineering and Manufacturing." Journal of Quality Technology 26, no. 1 (January 1994): 74–76. http://dx.doi.org/10.1080/00224065.1994.11979504.

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Brugger, Richard M., and Peter W. M. John. "Statistical Methods in Engineering and Quality Assurance." Technometrics 35, no. 1 (February 1993): 91. http://dx.doi.org/10.2307/1269300.

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Wardrop, Daniel M., and Peter W. M. John. "Statistical Methods in Engineering and Quality Assurance." American Statistician 47, no. 3 (August 1993): 234. http://dx.doi.org/10.2307/2684985.

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Bugger, Richard M. "Statistical Methods iu Engineering and Quality Assurance." Technometrics 35, no. 1 (February 1993): 91–92. http://dx.doi.org/10.1080/00401706.1993.10485004.

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Park, Sung H. "Statistical methods in engineering and quality assurance." Computational Statistics & Data Analysis 13, no. 1 (January 1992): 108. http://dx.doi.org/10.1016/0167-9473(92)90160-h.

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Dissertations / Theses on the topic "Engineering - Statistical methods"

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Marco, Almagro Lluís. "Statistical methods in Kansei engineering studies." Doctoral thesis, Universitat Politècnica de Catalunya, 2011. http://hdl.handle.net/10803/85059.

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Aquesta tesi doctoral tracta sobre Enginyeria Kansei (EK), una tècnica per traslladar emocions transmeses per productes en paràmetres tècnics, i sobre mètodes estadístics que poden beneficiar la disciplina. El propòsit bàsic de l'EK és descobrir de quina manera algunes propietats d'un producte transmeten certes emocions als seus usuaris. És un mètode quantitatiu, i les dades es recullen típicament fent servir qüestionaris. S'extreuen conclusions en analitzar les dades recollides, normalment usant algun tipus d'anàlisi de regressió. L'EK es pot situar en l'àrea de recerca del disseny emocional.
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Molaro, Mark Christopher. "Computational statistical methods in chemical engineering." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/111286.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 175-182).<br>Recent advances in theory and practice, have introduced a wide variety of tools from machine learning that can be applied to data intensive chemical engineering problems. This thesis covers applications of statistical learning spanning a range of relative importance of data versus existing detailed theory. In each application, the quantity and quality of data available from experimental systems are u
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Chang, Chia-Jung. "Statistical and engineering methods for model enhancement." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44766.

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Models which describe the performance of physical process are essential for quality prediction, experimental planning, process control and optimization. Engineering models developed based on the underlying physics/mechanics of the process such as analytic models or finite element models are widely used to capture the deterministic trend of the process. However, there usually exists stochastic randomness in the system which may introduce the discrepancy between physics-based model predictions and observations in reality. Alternatively, statistical models can be used to develop models to obta
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Walls, Frederick George 1976. "Topic detection through statistical methods." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80244.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (p. 77-79).<br>by Frederick George Walls.<br>M.Eng.
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Maas, Luis C. (Luis Carlos). "Statistical methods in ultrasonic tissue characterization." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/36456.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.<br>Includes bibliographical references (p. 88-93).<br>by Luis Carlos Maas III.<br>M.S.
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Yu, Huan. "New Statistical Methods for Simulation Output Analysis." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/4931.

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In this thesis, there are generally three contributions to the Ranking and Selection problem in discrete-event simulation area. Ranking and selection is an important problem when people want to select single or multiple best designs from alternative pool. There are two different types in discrete-event simulation: terminating simulation and steady-state simulation. For steady-state simulation, there is an initial trend before the data output enters into the steady-state, if we cannot start the simulation from steady state. We need to
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Betschart, Willie. "Applying intelligent statistical methods on biometric systems." Thesis, Blekinge Tekniska Högskola, Avdelningen för signalbehandling, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1694.

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This master’s thesis work was performed at Optimum Biometric Labs, OBL, located in Karlskrona, Sweden. Optimum Biometric Labs perform independent scenario evaluations to companies who develop biometric devices. The company has a product Optimum preConTM which is surveillance and diagnosis tool for biometric systems. This thesis work’s objective was to develop a conceptual model and implement it as an additional layer above the biometric layer with intelligence about the biometric users. The layer is influenced by the general procedure of biometrics in a multimodal behavioural way. It is workin
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Chandrasekaran, Venkat. "Convex optimization methods for graphs and statistical modeling." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66002.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 209-220).<br>An outstanding challenge in many problems throughout science and engineering is to succinctly characterize the relationships among a large number of interacting entities. Models based on graphs form one major thrust in this thesis, as graphs often provide a concise representation of the interactions among a large set of variables. A second major emphasis of this thesis are classes of
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Lingg, Andrew James. "Statistical Methods for Image Change Detection with Uncertainty." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1357249370.

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Ranger, Jeremy. "Adaptive image magnification using edge-directed and statistical methods." Thesis, University of Ottawa (Canada), 2004. http://hdl.handle.net/10393/26753.

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This thesis provides a comparison of two adaptive image magnification algorithms selected from the literature. Following implementation and experimentation with the algorithms, a number of improvements are proposed. The first selected algorithm takes an edge-directed approach by using an estimation of the edge map of the high-resolution image to guide the interpolation process. It was found that this algorithm suffered from certain inaccuracies in the edge detection stage. The proposed improvements focus on methods for increasing the accuracy of edge detection. The second selected algorithm ta
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Books on the topic "Engineering - Statistical methods"

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National Research Council (U.S.). Panel on Statistical Methods in Software Engineering. Statistical software engineering. Washington, D.C: National Academy Press, 1996.

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Singpurwalla, Nozer D., and Simon P. Wilson. Statistical Methods in Software Engineering. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-0565-4.

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Vining, G. Geoffrey. Statistical methods for engineers. 3rd ed. Boston, Mass: Cengage Learning, 2011.

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Gnedenko, Boris Vladimirovich. Statistical reliability engineering. New York: J. Wiley, 1999.

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Hahn, Gerald J. Statistical models in engineering. New York: Wiley, 1994.

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Vining, G. Geoffrey. Statistical methods for engineers. Pacific Grove, CA: Duxbury Press, 1998.

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A, Escobar Luis, ed. Statistical methods for reliability data. New York: Wiley, 1998.

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Ryan, Thomas P. Modern Engineering Statistics. New York: John Wiley & Sons, Ltd., 2007.

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1946-, Rhinehart R. Russell, ed. Applied engineering statistics. New York: M. Dekker, 1991.

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Bethea, Robert M. Applied engineering statistics. New York: M. Dekker, 1991.

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Book chapters on the topic "Engineering - Statistical methods"

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Richards, Keith L. "Statistical Methods for Engineers." In The Engineering Design Primer, 223–50. Boca Raton, FL : CRC Press/Taylor & Francis Group, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429264917-14.

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Yu, Weichuan, Baolin Wu, Tao Huang, Xiaoye Li, Kenneth Williams, and Hongyu Zhao. "Statistical Methods in Proteomics." In Springer Handbook of Engineering Statistics, 623–38. London: Springer London, 2006. http://dx.doi.org/10.1007/978-1-84628-288-1_34.

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Rosenberg, Jarrett. "Statistical Methods and Measurement." In Guide to Advanced Empirical Software Engineering, 155–84. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-044-5_6.

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Taniguchi, Masanobu, Tomoyuki Amano, Hiroaki Ogata, and Hiroyuki Taniai. "Various Methods for Financial Engineering." In Statistical Inference for Financial Engineering, 65–83. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03497-3_3.

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Bujorianu, Luminita Manuela. "Statistical Methods to Stochastic Reachability." In Communications and Control Engineering, 163–72. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2795-6_8.

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Jiang, Renyan. "Statistical Methods for Lifetime Data Analysis." In Springer Series in Reliability Engineering, 67–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47215-6_5.

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Mai, Qing, and Xin Zhang. "Statistical Methods for Tensor Data Analysis." In Springer Handbook of Engineering Statistics, 817–29. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-7503-2_39.

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Kenett, Ron S., Shelemyahu Zacks, and Peter Gedeck. "Advanced Methods of Statistical Process Control." In Statistics for Industry, Technology, and Engineering, 59–111. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28482-3_3.

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Singpurwalla, Nozer D., and Simon P. Wilson. "Statistical Analysis of Software Failure Data." In Statistical Methods in Software Engineering, 101–67. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-0565-4_4.

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Lima, Miguel F. M., and J. A. Tenreiro Machado. "A Statistical Approach for Tuning the Windowed Fourier Transform." In Mathematical Methods in Engineering, 269–81. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7183-3_25.

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Conference papers on the topic "Engineering - Statistical methods"

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Kitchenham, Barbara. "Robust statistical methods." In EASE '15: 19th International Conference on Evaluation and Assessment in Software Engineering. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2745802.2747956.

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Rossi, Nicola, and Meho-Saša Kovačević. "Statistical methods in geotechnics." In 4th Symposium on Doctoral Studies in Civil Engineering. University of Zagreb Faculty of Civil Engineering, 2018. http://dx.doi.org/10.5592/co/phdsym.2018.03.

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Julie, Hongki. "Application of pedagogy reflective in statistical methods course and practicum statistical methods." In INTERNATIONAL CONFERENCE ON MATHEMATICS: PURE, APPLIED AND COMPUTATION: Empowering Engineering using Mathematics. Author(s), 2017. http://dx.doi.org/10.1063/1.4994429.

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Standring, Jamie, and Prasad Malisetty. "Pump Noise Reduction Using Shainin Statistical Engineering Methods." In SAE 2001 Noise & Vibration Conference & Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2001. http://dx.doi.org/10.4271/2001-01-1542.

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Rodriguez, E., D. M. Tetzlaff, A. Mezzatesta, and E. Frost. "Estimating Rock Properties by Statistical Methods." In International Meeting on Petroleum Engineering. Society of Petroleum Engineers, 1988. http://dx.doi.org/10.2118/17603-ms.

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Luettgen, Mark R., William C. Karl, Alan S. Willsky, and Robert R. Tenney. "Multiresolution statistical methods in image analysis." In Applications in Optical Science and Engineering, edited by David P. Casasent. SPIE, 1992. http://dx.doi.org/10.1117/12.131582.

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Abella García, Ainoa, Lluís Marco-Almagro, and Laura Clèries. "Relationship between statistical methods and design, through Kansei engineering." In 9th International Conference on Kansei Engineering and Emotion Research (KEER2022). Kansei Engineering and Emotion Research (KEER), 2022. http://dx.doi.org/10.5821/conference-9788419184849.60.

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Both the disciplines of design and statistics have promoted projects and research with clear objectives in their field, but for the other discipline, they have been difficult or challenging to fully understand.&#x0D; &#x0D; In design, there are a large number of projects that provoke a reaction in spectators or users as they have a spectacular scope and impact, but at a statistical level, their results add little value. On the other hand, in some of the models and applications that are often used in statistics, the requirements are highly complex and numerous. This makes it difficult to put th
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Park, Gyuhae, Amanda C. Rutherford, Hoon Sohn, and Charles R. Farrar. "Damage Identification Using Impedance Methods Coupled With Statistical Classifiers." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-43179.

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This paper presents the use of statistically rigorous algorithms combined with active-sensing impedance methods for damage identification in engineering systems. In particular, we propose to use statistical pattern recognition methods to address damage classification and data mining issues associated with the examination of large numbers of impedance signals for health monitoring applications. The impedance-based structural health monitoring technique, which utilizes electromechanical coupling properties of piezoelectric materials, has shown feasibility for use in a variety of damage identific
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Trost, R. C., R. A. Ambros, and S. J. Robboy. "Statistical methods for morphometric analysis." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1988. http://dx.doi.org/10.1109/iembs.1988.94524.

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Ji, Xin-Yuan Serena, Shen Randy Kang, Yan-Ju Lisa Yu, and Wei-Ting Kary Chien. "A study on the statistical comparison methods for engineering applications." In 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2013. http://dx.doi.org/10.1109/ieem.2013.6962477.

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Reports on the topic "Engineering - Statistical methods"

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Utley, Dawn R. A Research and Analysis of Technology Trends, Engineering Management, and Statistical Methods. Fort Belvoir, VA: Defense Technical Information Center, February 2002. http://dx.doi.org/10.21236/ada399686.

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Nobile, F., Q. Ayoul-Guilmard, S. Ganesh, M. Nuñez, A. Kodakkal, C. Soriano, and R. Rossi. D6.5 Report on stochastic optimisation for wind engineering. Scipedia, 2022. http://dx.doi.org/10.23967/exaqute.2022.3.04.

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This report presents the latest methods of optimisation under uncertainties investigated in the ExaQUte project, and their applications to problems related to civil and wind engineering. The measure of risk throughout the report is the conditional value at risk. First, the reference method is presented: the derivation of sensitivities of the risk measure; their accurate computation; and lastly, a practical optimisation algorithm with adaptive statistical estimation. Second, this method is directly applied to a nonlinear relaxation oscillator (FitzHugh–Nagumo model) with numerical experiments t
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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, July 2020. http://dx.doi.org/10.52012/tyob9090.

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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden
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Singer, C., and D. Cox. Methods for testing transport models. [Departments of Nuclear Engineering and Statistics, Univ. of Illinois at Urbana[endash]Champaign]. Office of Scientific and Technical Information (OSTI), January 1993. http://dx.doi.org/10.2172/6886000.

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Lozev. L52022 Validation of Current Approaches for Girth Weld Defect Sizing Accuracy. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), July 2002. http://dx.doi.org/10.55274/r0011325.

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Computational tools based on probabilistic fracture mechanics have been developed to enable reliability-based fitness-for-service assessments of flawed girth welds. The same tools are readily adapted for establishing maximum allowable defect sizes to achieve targeted weld reliability. Sensitivity studies have shown that of the various input parameter uncertainties, measured defect height often has the greatest impact on the probabilities of both fracture and plastic collapse. A reduction in sizing uncertainty should thus dramatically improve predicted reliabilities. The increasing use of mecha
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Stuedlein, Armin, Ali Dadashiserej, and Amalesh Jana. Models for the Cyclic Resistance of Silts and Evaluation of Cyclic Failure during Subduction Zone Earthquakes. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, April 2023. http://dx.doi.org/10.55461/zkvv5271.

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This report describes several advances in the cyclic failure assessment of silt soils with immediate and practical benefit to the geotechnical earthquake engineering profession. First, a database of cyclic loading test data is assembled, evaluated, and used to assess trends in the curvature of the CRR-N (cyclic resistance ratio - the number of equivalent cycles) relationship. This effort culminated in a plasticity index-dependent function which can be used to estimate the exponent b in the power law describing cyclic resistance, and may be used to estimate the cyclic resistance of silt soils a
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RESEARCH PROGRESS ON FATIGUE PROPERTIES OF THE HIGHPERFORMANCE STEEL AND CONNECTION FORMS. The Hong Kong Institute of Steel Construction, August 2022. http://dx.doi.org/10.18057/icass2020.p.196.

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This paper reviews the current research status of fatigue performance of high-strength steels, introduces the basic theory of fatigue life and current design methods, the fatigue test data of a large number of high-strength steels are statistically collected, and the fatigue properties of high-strength steel base material and different connection structures are analyzed and evaluated. The research results show that high-strength steels with yield strength greater than 420MPa show better fatigue resistance, and the fatigue strength is significantly higher than the calculated value. The design c
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EFFECT OF RANDOM PRE-STRESSED FRICTION LOSS ON THE PERFORMANCE OF A SUSPEN-DOME STRUCTURE. The Hong Kong Institute of Steel Construction, March 2022. http://dx.doi.org/10.18057/ijasc.2022.18.1.5.

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The key to the high-efficiency performance of the suspen-dome structure is to apply the pre-stressed design value to the structure accurately. However, engineering practice has found that the use of tensioning hoop cables to apply the pre-stress will produce noticeable pre-stressed friction loss (PFL), which significantly affects the safety performance of the structure. In this paper, based on a 1:10 scaled-down experiment model of a suspen-dome structure with rolling cable-strut joint installed, the random PFL (RPFL) effect of the suspen-dome on structure performance was analyzed through a pr
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