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Journal articles on the topic 'Sensitivy analysis'

Author: Grafiati

Published: 10 March 2023

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1

Anders, Gilberto, and Itamar Borges. "Topological Analysis of the Molecular Charge Density and Impact Sensitivy Models of Energetic Molecules." Journal of Physical Chemistry A 115, no. 32 (August 18, 2011): 9055–68. http://dx.doi.org/10.1021/jp204562d.

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2

Rismawati, Rismawati, Lince Bulutoding, and Eka Suhartini. "PENGARUH ORGANIZATIONAL CITIZENSHIP BEHAVIOR, SELF EFFICACY DAN PROFESSIONAL ETHICAL SENSITIVY TERHADAP KINERJA AUDITOR DENGAN EMPLOYEE ENGAGEMENT SEBAGAI MODERASI." ISAFIR: Islamic Accounting and Finance Review 2, no. 1 (June 30, 2021): 98–107. http://dx.doi.org/10.24252/isafir.v2i1.19935.

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Penelitian ini menguji pengaruh Organizational Citizenship Behavior, Self Efficacy, dan Professional Ethical Sensitivity terhadap Kinerja Auditor dengan Employee Engangement sebagai Variabel Moderasi. Penelitian ini merupakan penelitian kuantitatif dengan pendekatan deskriptif dengan populasi berasal dari auditor yang bekerja pada Inspektorat Kota Makassar. Sampel penelitian sebanyak 30 auditor yang mengembalikan kuisioner dari jumlah 35 kuisioner yang disebar. Analisis data yang digunakan adalah analisis regresi berganda dan pemoderasi digunakan uji MRA (Moderated Regression Analysis). Hasil penelitian menunjukkan bahwa berdasarkan uji regresi berganda yang dilakukan membuktikan bahwa Organizational Citizenship Behavior, Self Efficacy, dan Professional Ethical Sensitivity berpengaruh positif dan siginfikan terhadap kinerja auditor. Pada uji regresi moderasi, ditemukan bahwa employee engangement mampu memoderasi pengaruh positif Organizational Citizenship Behavior dan Professional Ethical Sensitivity terhadap Kinerja Auditor, namun tidak mampu memoderasi pengaruh positif self efficacy terhadap Kinerja Auditor.

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3

Taji, Kouichi, and Keiji Matsumoto. "INVERSE SENSITIVE ANALYSIS OF PAIRWISE COMPARISON MATRICES." Journal of the Operations Research Society of Japan 49, no. 4 (2006): 332–41. http://dx.doi.org/10.15807/jorsj.49.332.

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4

Riveros, Bruno, Mariana Rosim, Gabriel Pedro, Rosa Lucchetta, and Marcelo Nita. "Análise de custo-efetividade e a análise de sensibilidade, um roteiro para execução de uma abordagem probabilística: Introdução à análise de sensibilidade probabilística (Parte I)." Jornal de Assistência Farmacêutica e Farmacoeconomia 1, no. 2 (December 2016): 33–38. http://dx.doi.org/10.22563/2525-7323.2016.v1.n2.p.33-38.

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5

HORVATH, Gabor, and Norbert PATAKI. "IMPROVING THE PRECISION OF FLOW-SENSITIVE LIFETIME ANALYSIS." Acta Electrotechnica et Informatica 20, no. 4 (January 21, 2020): 10–18. http://dx.doi.org/10.15546/aeei-2020-0020.

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Object lifetimes are a common source of bugs in C++ that can cause crashes, unexpected behavior, or even security vulnerabilities. Herb Sutter, the chair of the C++ standard committee proposed a flow-sensitive analysis to catch lifetime errors statically. Sadly, this analysis is prone to false positives unless the author follows some specific guidelines. We developed mitigations to eliminate some classes of false positives to make it easier to write conforming code. The first mitigation fixes a common false positive from a frequently used coding pattern by introducing local path-sensitivity. The second one is a filter based on reaching definitions and dominance algorithms to remove reports that might be the result of analyzing infeasible paths. We tested the effectiveness of the methods on the open source Google Fuchsia project.

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6

Kucherenko, D. Yu. "APPLICATION OF GLUTAMATE-SENSITIVE BIOSENSOR FOR ANALYSIS OF FOODSTUFF." Biotechnologia Acta 11, no. 4 (August 2018): 57–67. http://dx.doi.org/10.15407/biotech11.04.057.

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7

Yunanto, Muhamad, and Henny Medyawati. "Fiscal Policy and Monetary Policy: Sensitivity Analysis." International Journal of Trade, Economics and Finance 6, no. 2 (April 2015): 79–84. http://dx.doi.org/10.7763/ijtef.2015.v6.447.

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8

Dragičević, N., B. Karleuša, and N. Ožanić. "Erosion Potential Method (Gavrilović method) sensitivity analysis." Soil and Water Research 12, No. 1 (January 18, 2017): 51–59. http://dx.doi.org/10.17221/27/2016-swr.

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In recent decades, various methods for erosion intensity and sediment production assessment have been developed. The necessity for better model performance has led to the more frequent application of the method sensitivity and uncertainty assessments in order to decrease errors that arise from the model concept and its main assumptions. The analysis presented in this paper refers to the application of the Gavrilović method (Erosion Potential Method), an empirical and semi-quantitative method that can estimate the amount of sediment production and sediment transport as well as the erosion intensity and indicate the areas potentially threatened by erosion. The emphasis in this paper is given upon the method sensitivity analysis that has not previously been conducted for the Gavrilović method. The sensitivity analysis was conducted for fourteen different parameters included in the method, all in relation to different model outputs. Each parameter was perceived and discussed individually in relation to its effect upon the method outputs, and ranked into categories depending on their influence on one or more model outputs. The objective of the analysis was to explore the constraints of the Gavrilović method and the method response to changes deriving from the each individual parameter in an attempt to provide a better understanding of the method, the weight and the contribution of each parameter in the overall method. The parameters that could potentially be used in future research, for method modification and calibration in areas with different catchment characteristics (e.g. climate, geological, etc.) were identified. The most sensitive model parameters resulting from conducted sensitivity analysis for the Gavrilović method are also those considered to be significant in the scientific literature on erosion. The Gavrilović method sensitivity analysis has been done on a case study for the Dubracina catchment area, Croatia.

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9

Qichang An, Qichang An, Jingxu Zhang Jingxu Zhang, Fei Yang Fei Yang, and Hongchao Zhao Hongchao Zhao. "Normalized point source sensitivity analysis in GSSM prototype." Chinese Optics Letters 15, no. 11 (2017): 111202. http://dx.doi.org/10.3788/col201715.111202.

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10

Juhl, C. F. "A Context-Sensitive Liar." Analysis 57, no. 3 (July 1, 1997): 202–4. http://dx.doi.org/10.1093/analys/57.3.202.

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11

Kavka, M., M. Mimra, and F. Kumhála. "Sensitivity analysis of key operating parameters of combine harvesters." Research in Agricultural Engineering 62, No. 3 (August 30, 2016): 113–21. http://dx.doi.org/10.17221/48/2015-rae.

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The sensitivity analysis of key operating parameters on the average annual sub-profit in a group of three combine harvesters operating in companies providing agricultural services were analysed. Based on the results of the cost analysis, the following key operating parameters with the greatest influence on the costs were identified: the purchase price of the machine, the price of fuel, maintenance costs, personnel costs and annual performance. These parameters were used in the sensitivity analysis to investigate their effect on unit costs. Changing the above-mentioned parameters is calculated within ± 30% from their mean value. To perform a sensitivity analysis of the average annual sub-profit of combine harvesters, the unit price of mechanized work was additionally used. The results showed that greatest impact on both the average annual earnings of combines operation and on the changes in unit cost was those of the annual performance of the combine harvester, combine harvester purchase price and the cost of fuel. On the other hand, maintenance and personnel costs had a smaller influence concerning these changes of parameters.

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12

Liu, Zhe, Fenghe Tao, and Changzhi Jia. "Reliability Sensitivity Analysis of Vehicle Components and Architecture Optimization." International Journal of Materials, Mechanics and Manufacturing 5, no. 2 (May 2017): 106–12. http://dx.doi.org/10.18178/ijmmm.2017.5.2.299.

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13

Zhou, Peiyuan, and Jinling Wang. "Stochastic Ionosphere Models for Precise GNSS Positioning: Sensitivity Analysis." Journal of Global Positioning Systems 12, no. 1 (June 30, 2013): 53–60. http://dx.doi.org/10.5081/jgps.12.1.53.

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14

Doyle, James D., Clark Amerault, and Carolyn A. Reynolds. "Sensitivity analysis of mountain waves using an adjoint model." Meteorologische Zeitschrift 16, no. 6 (December 17, 2007): 607–20. http://dx.doi.org/10.1127/0941-2948/2007/0236.

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15

Liu, Yongsheng. "Sensitivity analysis and proportioning design of rock burst similar materials." Functional materials 24, no. 3 (September 29, 2017): 005–500. http://dx.doi.org/10.15407/fm24.03.496.

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16

Dzantiev, B. B. "MODERN TECHNIQUES OF IMMUNOCHEMICAL ANALYSIS: INTEGRATION OF SENSITIVITY AND RAPIDITY." Biotechnologia Acta 6, no. 4 (2013): 94–104. http://dx.doi.org/10.15407/biotech6.04.094.

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17

MacFarlane, J. "Knowledge laundering: testimony and sensitive invariantism." Analysis 65, no. 2 (April 1, 2005): 132–38. http://dx.doi.org/10.1093/analys/65.2.132.

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18

Koçak, Hüseyin, and Kenneth J. Palmer. "Lyapunov Exponents and Sensitive Dependence." Journal of Dynamics and Differential Equations 22, no. 3 (April 13, 2010): 381–98. http://dx.doi.org/10.1007/s10884-010-9169-y.

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19

Ibrahim, Abdulkareem Afolabi. "Stability and Sensitivity Analysis of Tumor-induceimmune Suppression with Time Delay." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 1321–31. http://dx.doi.org/10.5373/jardcs/v12sp7/20202232.

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20

Safiullina, L. F., I. M. Gubaydullin, K. F. Koledina, and R. Z. Zaynullin. "Sensitivity analysis of the mathematical model of catalytic reforming of gasoline." Computational Mathematics and Information Technologies 3, no. 2 (2019): 43–53. http://dx.doi.org/10.23947/2587-8999-2019-2-2-43-53.

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21

Pattanaik, Priyabrata. "An Analysis of Price Sensitivity of Smart Phone Purchase in India." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (October 25, 2019): 359–63. http://dx.doi.org/10.5373/jardcs/v11sp10/20192813.

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22

Park, Jae Kweon, Jio Song, Eung Take Lee, Ji Hyun Lee, and Hyun Lee. "Matrix Sensitivity and Interpretation for Precise Molecular Weight Analysis of Chitosan Hydrolysates." Journal of Chitin and Chitosan 27, no. 2 (June 30, 2022): 94–103. http://dx.doi.org/10.17642/jcc.27.2.5.

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23

Rivera-Martínez, Mario Arturo, Geovanni Hernández-Galvez, Omar Sarracino-Martínez, Luis Ixtlilco-Cortés, Alina Juantorena-Ugás, Ulises Ivan Batalla-Nolasco, and David Becerra-García. "Análisis de sensibilidad de sistemas fotovoltaicos conectados a la red eléctrica: Caso de estudio en Guerrero, México." Ingeniería, investigación y tecnología 18, no. 3 (July 1, 2017): 293–305. http://dx.doi.org/10.22201/fi.25940732e.2017.18n3.026.

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24

Wongchanapai, Suranat, Hiroshi Iwai, Motohiro Saito, and Hideo Yoshida. "F124 Sensitivity Analysis of a Direct-Biogas SOFC-MGT Hybrid CHP System." Proceedings of the Thermal Engineering Conference 2012 (2012): 181–82. http://dx.doi.org/10.1299/jsmeted.2012.181.

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25

Mogha, SK, SP Yadav, and SP Singh. "Performance Evaluation of Indian Private Hospitals Using DEA Approach with Sensitivity Analysis." International Journal of Advances in Management and Economics 1, no. 2 (March 2, 2012): 01–12. http://dx.doi.org/10.31270/ijame/01/02/2012/01.

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26

Cai, Hao, Xingtao Yu, Qian Chu, Zhiqiang Jin, Bo Lin, and Guanghui Wang. "Hollow-core fiber-based Raman probe extension kit for in situ and sensitive ultramicro-analysis." Chinese Optics Letters 17, no. 11 (2019): 110601. http://dx.doi.org/10.3788/col201917.110601.

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27

Kaushik, A. "Gender-sensitive analysis." British Dental Journal 233, no. 2 (July 22, 2022): 69. http://dx.doi.org/10.1038/s41415-022-4510-5.

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28

Li, Jie, and Tao Yu. "On mean sensitive tuples." Journal of Differential Equations 297 (October 2021): 175–200. http://dx.doi.org/10.1016/j.jde.2021.06.032.

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29

Ramalingam, G. "Context-sensitive synchronization-sensitive analysis is undecidable." ACM Transactions on Programming Languages and Systems 22, no. 2 (March 2000): 416–30. http://dx.doi.org/10.1145/349214.349241.

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30

Jian-hong LIAO, 廖健宏, 张昂 Ang ZHANG, 王进起 Jin-qi WANG, 朱强 Qiang ZHU, and 熊德智 De-zhi XIONG. "四通道超稳腔的振动分析及热分析." Acta Sinica Quantum Optica 27, no. 2 (2021): 169. http://dx.doi.org/10.3788/jqo20212702.0901.

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31

Romero-Arismendi, Nestor, Pedro Martínez-Ortiz, José H. Espina-Hernández, and José Pérez-Benítez. "Análisis de la sensibilidad, respuesta de pequeña señal y respuesta dinámica de un sensor GMR." Científica 25, no. 2 (July 1, 2021): 1–14. http://dx.doi.org/10.46842/ipn.cien.v25n2a01.

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En este trabajo se lleva a cabo el análisis de la sensibilidad de un sensor magnético, basado en el fenómeno de magnetorresistencia gigante (GMR), cuando se utiliza en la medición de campos magnéticos variantes en el tiempo en superposición con componentes estáticas. La característica de transferencia del sensor GMR se obtuvo experimentalmente midiendo el campo magnético generado por una bobina de Helmholtz. A partir de la característica de transferencia experimental se obtuvo computacionalmente la respuesta de sensibilidad del sensor GMR y posteriormente se validó experimentalmente. Se determinó una nueva región de operación del sensor GMR en la respuesta de sensibilidad del sensor GMR, la cual tiene un comportamiento lineal. Los resultados demuestran que, es indispensable utilizar un campo de polarización para garantizar un mejor desempeño del sensor GMR en las mediciones de campos magnéticos pequeños. El valor del campo de polarización utilizado depende del tipo de campo magnético en función del tiempo que se vaya a medir (AC o DC). Finalmente, en este artículo se presentan y proponen los correspondientes rangos de valores de los campos magnéticos de polarización.

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32

Majkrzak, Marcin. "Wpływ zmian wybranych parametrów pokładu węgla kamiennego na przebieg i efektywność procesu eksploatacji metanu." Nafta-Gaz 75, no. 5 (May 2019): 254–64. http://dx.doi.org/10.18668/ng.2019.05.03.

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33

Kim. "Sensitivity analysis of tunnel stability with a consideration of an excavation damaged zone." Journal of Korean Tunnelling and Underground Space Associa 16, no. 1 (2014): 091. http://dx.doi.org/10.9711/ktaj.2014.16.1.091.

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34

G Hamlet, C., S. M Jayaratne, and P. A Sadd. "Rapid, sensitive and selective analysis of acrylamide in cereal products using bromination and GC/MS/MS." Czech Journal of Food Sciences 22, SI - Chem. Reactions in Foods V (January 1, 2004): S290—S293. http://dx.doi.org/10.17221/10684-cjfs.

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A rapid and sensitive method has been developed and validated for the analysis of acrylamide in cereal products. A kinetic study showed that a quantitative bromination of acrylamide in cereal extracts could be achieved within 25 min at room temperature. By using GC/MS/MS an increase in signal to noise of between 70 to 100 could be achieved for samples with minimal clean up compared to conventional selected ion monitoring. Results obtained from the analysis of a FAPAS cereal test material showed good agreement with the assigned value.

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35

He, Lianfa, Xinhua Yan, and Lingshu Wang. "Weak-mixing implies sensitive dependence." Journal of Mathematical Analysis and Applications 299, no. 1 (November 2004): 300–304. http://dx.doi.org/10.1016/j.jmaa.2004.06.066.

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36

Banks, H., K. Bekele-Maxwell, L. Bociu, M. Noorman, and K. Tillman. "THE COMPLEX-STEP METHOD FOR SENSITIVITY ANALYSIS OF NON-SMOOTH PROBLEMS ARISING IN BIOLOGY." Eurasian Journal of Mathematical and Computer Applications 3, no. 1 (2015): 16–68. http://dx.doi.org/10.32523/2306-3172-2015-3-3-16-68.

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37

Nunes, Gustavo Henrique, and Thalita Gorban Ferreira Giglio. "Análise de sensibilidade de variáveis termofísicas de habitações brasileiras sob a influência das mudanças climáticas." Ambiente Construído 22, no. 4 (December 2022): 91–120. http://dx.doi.org/10.1590/s1678-86212022000400630.

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Resumo Este estudo teve como objetivo determinar índices de sensibilidade global de variáveis termofísicasno desempenho térmico de habitações em Belém, Brasília, São Paulo e Curitiba, considerando os efeitos das mudanças climáticas. Para tanto, o desempenho térmico de um dormitório foi analisado em diferentes períodosclimáticos, a partir de progressões obtidas por meio da ferramenta CCWorldWeatherGen, para os intervalos dos anos 2020 (representa 2011 a 2040), 2050 (representa 2041 a 2070) e 2080 (representa 2071 a 2100), de acordo com o cenário de emissões A2 do Painel Intergovernamental sobre Mudanças Climáticas. Os índices de sensibilidade de Morris indicaram que as mudanças climáticas, além de influenciarem no desempenho térmico do ambiente construído, influenciam na importância das variáveis termofísicas, principalmente em cidades com climas mais amenos. Em Belém, o fator de ventilação foi mais importante; em Brasília, destacaram-se a transmitância térmica das paredes e o fator de ventilação; e em São Paulo e Curitiba, destacaram-se a absortância solar da cobertura, a orientação solar e o fator de ventilação. Diante de variações determinantes nos índices de sensibilidade ao longo dos anos, conclui-se que o projeto de edificações deve, necessariamente, considerar projeções de mudanças climáticas, para que o ambiente construído possua resiliência em seu desempenho.

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38

Liu, Maolong, Nejdet Erkan, Koji Okamoto, and Naoto Kasahara. "ICONE23-1712 SENSITIVITY ANALYSIS OF THE BWR PASSIVE DEPRESSURIZATION SYSTEM UNDER SEVERE ACCIDENT CONDITIONS." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2015.23 (2015): _ICONE23–1—_ICONE23–1. http://dx.doi.org/10.1299/jsmeicone.2015.23._icone23-1_353.

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39

Jovanovic-Dolecek, Gordana, and Sanjit Mitra. "Symbolic sensitivity analysis of the newsecond-order iir structure." Ingeniería, investigación y tecnología 9, no. 1 (January 1, 2008): 59–65. http://dx.doi.org/10.22201/fi.25940732e.2008.09n1.005.

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40

ATALAY, Ayşe Özge. "Ceza Muhakemesi Hukukunda Moleküler Genetik İncelemelerin Özel Nitelikli Kişisel Verilerin Korunması Açısından Değerlendirilmesi." Journal of Penal Law & Criminology 7, no. 2 (January 13, 2020): 127–84. http://dx.doi.org/10.26650/jplc2019-0018.

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41

Lu, Jingbo, Dongjie He, and Jingling Xue. "Eagle." ACM Transactions on Software Engineering and Methodology 30, no. 4 (July 2021): 1–46. http://dx.doi.org/10.1145/3450492.

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Object sensitivity is widely used as a context abstraction for computing the points-to information context-sensitively for object-oriented programming languages such as Java. Due to the combinatorial explosion of contexts in large object-oriented programs, k -object-sensitive pointer analysis (under k -limiting), denoted k -obj , is often inefficient even when it is scalable for small values of k , where k ⩽ 2 holds typically. A recent popular approach for accelerating k -obj trades precision for efficiency by instructing k -obj to analyze only some methods in a program context-sensitively, determined heuristically by a pre-analysis. In this article, we investigate how to develop a fundamentally different approach, Eagle , for designing a pre-analysis that can make k -obj run significantly faster while maintaining its precision. The novelty of Eagle is to enable k -obj to analyze a method with partial context sensitivity (i.e., context-sensitively for only some of its selected variables/allocation sites) by solving a context-free-language (CFL) reachability problem based on a new CFL-reachability formulation of k -obj . By regularizing one CFL for specifying field accesses and using another CFL for specifying method calls, we have formulated Eagle as a fully context-sensitive taint analysis (without k -limiting) that is both effective (by selecting the variables/allocation sites to be analyzed by k -obj context-insensitively so as to reduce the number of context-sensitive facts inferred by k -obj in the program) and efficient (by running linearly in terms of the number of pointer assignment edges in the program). As Eagle represents the first precision-preserving pre-analysis, our evaluation focuses on demonstrating its significant performance benefits in accelerating k -obj for a set of popular Java benchmarks and applications, with call graph construction, may-fail-casting, and polymorphic call detection as three important client analyses.

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42

Sharma, Roshan, and Bjørn Glemmestad. "Uncertainty and Sensitivity Analysis for a Model of an Electric Submersible Pump Lifted Oil Field." International Journal of Modeling and Optimization 4, no. 4 (August 2014): 278–86. http://dx.doi.org/10.7763/ijmo.2014.v4.386.

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43

Werner, Francisco E., Brian R. MacKenzie, R. Ian Perry, R. Gregory Lough, Christopher E. Naimie, Brian O. Blaton, and John A. Quinlan. "Larval trophodynamics, turbulence, and drift on Georges Bank: A sensitivity analysis of Cod and Haddock." Scientia Marina 65, S1 (July 30, 2001): 99–115. http://dx.doi.org/10.3989/scimar.2001.65s199.

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44

Karki, Ashok, Santosh Bhattarai, Pradhumna Joshi, Mukesh Kafle, and Rajesh Bhattarai. "DAM BREACH ANALYSIS AND PARAMETER SENSITIVITY ANALYSIS ALONG A RIVER REACH USING HECRAS." Stavební obzor - Civil Engineering Journal 31, no. 4 (December 31, 2022): 571–85. http://dx.doi.org/10.14311/cej.2022.04.0043.

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A dam break is a low-probability, high risk catastrophe event that is extremely destructive and has a substantial negative socio-economic impact on downstream and nearby areas. Simulating dam breach and analyzing flood propagation downstream from those events is vital for identifying and minimizing the risks associated downstream of dam location. This study is intended to anlayse the effect of overtopping failure of dam for two scenario (a) base-case scenario (scenario with average value of dam breach parameters from their range) and (b) worst case scenario (the breach with largest geometry, shortest formation time and highest peak outflow magnitude). Further, a hydrodyanmic modelling is perfomed to investigate the sensitivity analysis (local and global) of five dam breach parameters (dam breach elevation, dam breach width, breach formation time, weir coefficient, trigger failure elevation) on breach outflow in a proposed hydropower project located in Nepal. Aeronautical Reconnaissance Coverage Geographic Information System (ArcGIS), Hydraulic Engineering Center River Analysis System (HEC-RAS) and OriginPro 2022b are utilized to analyse the effect of dam breach and parameter sensitivity. Generation of outflow hydrograph shows that worst case scenario has devasting effect downstream with innudation of 1047 of househols and 50.83 kilometers of roads. The breach velocty was recorded as 15.16 m/s and 20.85 m/s for base and worst case respectively. The minimum depth and maximum depth of flooding downstream from dam location was found to be 24.51 m and 73.6 m for base case and 47.43 m and 106.75 m for worst case. Due to backwater effect at Bheri river, peak flow at 14 km downstream from dam reduces significantly to 124852.57 m3/s and 244204.41 m3/s for base and worst case respectively. From local sensitivty analysis it has been found that, dam breach elevation is more sensitive and triggering failure elevation is less sensitive for peak outflow hydrograph. Whereas, dam breach width seems more sensitive and TFE seems least sensitive for peak outflow using Monte Carlo Simulation for gloal sensitivity.

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45

Agarwal, Ravi P., Jewgeni H. Dshalalow, and Donal O'Regan. "Time sensitive functionals of marked Cox processes." Journal of Mathematical Analysis and Applications 293, no. 1 (May 2004): 14–27. http://dx.doi.org/10.1016/j.jmaa.2003.12.030.

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46

Vollmer, J., J. Peinke, and A. Okniński. "Dweiltime Analysis of Symmetry-Breaking Dynamical Systems." Zeitschrift für Naturforschung A 50, no. 12 (December 1, 1995): 1117–22. http://dx.doi.org/10.1515/zna-1995-1209.

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Abstract Dweiltime analysis is known to characterize saddles giving rise to chaotic scattering. In the present paper it is used to characterize the dependence on initial conditions of the attractor approached by a trajectory in dissipative systems described by one-dimensional, noninvertible mappings which show symmetry breaking. There may be symmetry-related attractors in these systems, and which attractor is approached may depend sensitively on the initial conditions. Dwell-time analysis is useful in this context because it allows to visualize in another way the repellers on the basin boundary which cause this sensitive dependence.

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47

Shen, Ren Jie, Yan Yan Liang, and Jing Zhang. "Sensitive Analysis of Water-Network." Advanced Materials Research 433-440 (January 2012): 1302–6. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.1302.

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As a weak point, bottleneck plays a crucial role in improving the property of the whole water system. In this paper, sensitivity computation formula is defined and corresponding mathematical model is established to confirm the bottleneck of water network. And the case proves that the bottleneck streams and units can be easily confirmed by the method in this paper.

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48

Jianwen Zhu and S. Calman. "Context sensitive symbolic pointer analysis." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 24, no. 4 (April 2005): 516–31. http://dx.doi.org/10.1109/tcad.2005.844092.

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Landman, P. E., and J. M. Rabaey. "Activity-sensitive architectural power analysis." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 15, no. 6 (June 1996): 571–87. http://dx.doi.org/10.1109/43.503928.

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50

Wittmann-Liebold, B. "High-sensitive protein sequence analysis." Pure and Applied Chemistry 64, no. 4 (January 1, 1992): 537–43. http://dx.doi.org/10.1351/pac199264040537.

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