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Journal articles on the topic 'Micro-models'

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Author: Grafiati
Published: 14 March 2023

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1

Maske, Ms Swapnali S. "Wireless Micro-Sensor Network Models." IOSR Journal of Computer Engineering 6, no. 3 (2012): 09–14. http://dx.doi.org/10.9790/0661-0630914.

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2

Glenn, Floyd. "The Case for Micro-models." Proceedings of the Human Factors Society Annual Meeting 33, no. 18 (October 1989): 1228–32. http://dx.doi.org/10.1177/154193128903301813.

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This paper examines the appropriate role of human performance micro-models in simulations of human-machine system operations. Requirements for general human micro-models are considered relative to the objectives of simulation studies, the conditions under which simulations are constructed and used, the status of human performance data bases and models, and the features provided with general-purpose simulation software. This investigation focuses particularly on a new simulation tool for simulating human-machine systems; it is known as the Human Operator Simulator – Version V (HOS-V). A general design principle of HOS-V has been to provide embedded human performance micro-models for the basic performance processes that seem most pervasive and interactive with other processes. These include representations for processes of body movement, cognition, and attention. Key to these representations are the substructures in each area. Body movement models describe locations of body parts and constraints on their movement. Cognition models describe how the human processes information through perception, memory, decision-making, and action initiation. The attention model describes how a limited attentional resource is allocated to the various body movement and cognition processes, each of which has a defined attentional requirement. Plans for implementation of micro-model components of HOS-V are discussed.
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3

Kowerski, Mieczysław, Jarosław Bielak, and Mariusz Poninkiewicz. "Financial micro-macro qualitative response models." Annales Universitatis Mariae Curie-Skłodowska, sectio H, Oeconomia 48, no. 3 (January 16, 2015): 167. http://dx.doi.org/10.17951/h.2015.48.3.167.

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4

Paarsch, Harry J. "Micro-Economic Models of Beef Supply." Canadian Journal of Economics 18, no. 3 (August 1985): 636. http://dx.doi.org/10.2307/135025.

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5

C., D., J. Stillwell, and J. Congdon. "Migration Models: Macro and Micro Approaches." Population (French Edition) 47, no. 3 (May 1992): 795. http://dx.doi.org/10.2307/1533753.

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6

Wagner, Michael. "Migration Models: Macro and Micro Approaches." Population Studies 47, no. 2 (July 1, 1993): 375–77. http://dx.doi.org/10.1080/0032472031000147186.

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7

Perera, A., R. Mazighi, B. Kežić-Lovrincević, and N. P. Pham. "Mixture models with weak micro-heterogeneity." Molecular Physics 112, no. 9-10 (March 3, 2014): 1262–72. http://dx.doi.org/10.1080/00268976.2014.889859.

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8

Federico, S., and W. Herzog. "Micro-structural models of articular cartilage." Journal of Biomechanics 39 (January 2006): S407. http://dx.doi.org/10.1016/s0021-9290(06)84652-x.

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9

Ronning, Gerd. "Microeconometric models and anonymized micro data." Allgemeines Statistisches Archiv 90, no. 1 (March 2006): 153–66. http://dx.doi.org/10.1007/s10182-006-0227-z.

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10

Jurado, Francisco. "Modelling micro-turbines using Hammerstein models." International Journal of Energy Research 29, no. 9 (2005): 841–55. http://dx.doi.org/10.1002/er.1102.

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11

Ascarya, Ascarya, and Ali Sakti. "Designing micro-fintech models for Islamic micro financial institutions in Indonesia." International Journal of Islamic and Middle Eastern Finance and Management 15, no. 2 (March 16, 2022): 236–54. http://dx.doi.org/10.1108/imefm-05-2020-0233.

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Purpose This study aims to design appropriate micro-fintech models for Islamic microfinance institutions (IMFIs), especially Baitul Maal wat Tamwil (BMT) in Indonesia, thus enabling BMT to combine Islamic social and commercial microfinance optimally. Design/methodology/approach This study uses the analytic network process and Delphi methods, with three groups of experts as the respondents, namely, academician-regulators, BMT practitioners and Fintech practitioners. Findings The first results show that the micro-fintech tools needed by IMFI/BMT are digital banking, payment, peer-to-peer (P2P) financing, P2P social and e-commerce. These could be developed by a BMT alone or with an APEX or Association, which could also collaborate with an existing fintech company that specialises in micro-fintech, applying the offline to online approach. This means that commercial funding, as well as social fundraising of zakat and waqf, would be conducted online, whereas commercial financing for micro and small enterprise customers and the disbursement of zakat and waqf would be conducted offline. The second results show that the limited open ecosystem and hybrid ecosystem are the most appropriate micro-fintech ecosystems for IMFIs/BMT, with various alternative models. In addition, the private closed ecosystem preferred by BMT would be feasible if all criteria show improvement in the future. Research limitations/implications This study is qualitative in nature. The methods used have limitations, meaning the models could be improved by incorporating other methods. Moreover, the case and respondents are all Indonesian, which means that the results may only be applicable to BMTs in Indonesia. Practical implications A BMT and/or BMT association could immediately apply micro-fintech with a limited open ecosystem, while in the future, they could apply micro-fintech with a private closed ecosystem. Social implications The micro-fintech model could be used to optimise the collections of zakat, infaq and waqf, meaning BMT could provide more social programmes for those in need. Originality/value The growth of fintech in Islamic microfinance has occurred only recently, while only a limited number of studies have been conducted; therefore, no study exists on the development of a micro-fintech model appropriate for IMFIs, especially BMT.
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12

Cricri, Gabriele, and Raimondo Luciano. "Micro- and macro-failure models of heterogeneous media with micro-structure." Simulation Modelling Practice and Theory 11, no. 5-6 (August 2003): 433–48. http://dx.doi.org/10.1016/s1569-190x(03)00052-2.

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13

Turcotte, Donald L., William I. Newman, and Robert Shcherbakov. "Micro and macroscopic models of rock fracture." Geophysical Journal International 152, no. 3 (March 2003): 718–28. http://dx.doi.org/10.1046/j.1365-246x.2003.01884.x.

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14

Khungurn, Pramook, Daniel Schroeder, Shuang Zhao, Kavita Bala, and Steve Marschner. "Matching Real Fabrics with Micro-Appearance Models." ACM Transactions on Graphics 35, no. 1 (December 29, 2015): 1–26. http://dx.doi.org/10.1145/2818648.

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15

Nicola, PierCarlo. "Micro-founded macro-models and labour market☆." Chaos, Solitons & Fractals 29, no. 3 (August 2006): 671–80. http://dx.doi.org/10.1016/j.chaos.2005.08.098.

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16

WANG, XIAOBING, and JENIFER PIESSE. "THE MICRO-FOUNDATIONS OF DUAL ECONOMY MODELS*." Manchester School 81, no. 1 (September 19, 2011): 80–101. http://dx.doi.org/10.1111/j.1467-9957.2011.02263.x.

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17

Ahokangas, Petri, Marja Matinmikko-Blue, Seppo Yrjola, Veikko Seppanen, Heikki Hammainen, Risto Jurva, and Matti Latva-aho. "Business Models for Local 5G Micro Operators." IEEE Transactions on Cognitive Communications and Networking 5, no. 3 (September 2019): 730–40. http://dx.doi.org/10.1109/tccn.2019.2902547.

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18

Pedley, T. J. "Spherical squirmers: models for swimming micro-organisms." IMA Journal of Applied Mathematics 81, no. 3 (June 2016): 488–521. http://dx.doi.org/10.1093/imamat/hxw030.

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19

Gontier, E., P. Barberet, Y. Barbotteau, K. Gáspár, C. Habchi, J. Hunyadi, S. Incerti, et al. "Micro-PIXE characterization of different skin models." X-Ray Spectrometry 34, no. 4 (2005): 381–88. http://dx.doi.org/10.1002/xrs.852.

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20

Cueto, E., M. Laso, and F. Chinesta. "MESHLESS STOCHASTIC SIMULATION OF MICRO-MACROKINETIC THEORY MODELS." International Journal for Multiscale Computational Engineering 9, no. 1 (2011): 1–16. http://dx.doi.org/10.1615/intjmultcompeng.v9.i1.20.

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21

Kumar, T. S. Anand, V. Praseeda Sanu, and Jeyanth K. Newport. "Transaction Cost Reduction Models For Micro Finance Institutions." Journal of Commerce and Management Thought 6, no. 1 (2015): 32. http://dx.doi.org/10.5958/0976-478x.2015.00002.6.

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22

Imbens, G. W., and T. Lancaster. "Combining Micro and Macro Data in Microeconometric Models." Review of Economic Studies 61, no. 4 (October 1, 1994): 655–80. http://dx.doi.org/10.2307/2297913.

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23

Boutin, Claude, Francesco dell’Isola, Ivan Giorgio, and Luca Placidi. "Linear pantographic sheets: Asymptotic micro-macro models identification." Mathematics and Mechanics of Complex Systems 5, no. 2 (May 13, 2017): 127–62. http://dx.doi.org/10.2140/memocs.2017.5.127.

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24

Morini, G. "Micro and Macro Models of the Sweet Receptor." Chemical Senses 30, Supplement 1 (January 1, 2005): i86—i87. http://dx.doi.org/10.1093/chemse/bjh126.

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25

Ramadan, Qasem, and Martin A. M. Gijs. "In vitro micro-physiological models for translational immunology." Lab on a Chip 15, no. 3 (2015): 614–36. http://dx.doi.org/10.1039/c4lc01271b.

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26

Menciassi, A., A. Eisinberg, I. Izzo, and P. Dario. "From “Macro” to “Micro” Manipulation: Models and Experiments." IEEE/ASME Transactions on Mechatronics 9, no. 2 (June 2004): 311–20. http://dx.doi.org/10.1109/tmech.2004.828657.

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27

SANO, Masato, Masahiro NAKAJIMA, Masaru TAKEUCHI, Yasuhisa HASEGAWA, Tomonori NAKANO, Shigeru KURIMOTO, and Hitoshi HIRATA. "Retaining structure of micro electrode for rodent models." Proceedings of the Bioengineering Conference Annual Meeting of BED/JSME 2017.29 (2017): 2G32. http://dx.doi.org/10.1299/jsmebio.2017.29.2g32.

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28

Tilak, Sameer, Nael B. Abu-Ghazaleh, and Wendi Heinzelman. "A taxonomy of wireless micro-sensor network models." ACM SIGMOBILE Mobile Computing and Communications Review 6, no. 2 (April 2002): 28–36. http://dx.doi.org/10.1145/565702.565708.

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29

Showalter, R. E., and N. J. Walkington. "Micro-structure models of diffusion in fissured media." Journal of Mathematical Analysis and Applications 155, no. 1 (February 1991): 1–20. http://dx.doi.org/10.1016/0022-247x(91)90023-s.

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30

Ren, Xiaodan, Jiun-Shyan Chen, Jie Li, T. R. Slawson, and M. J. Roth. "Micro-cracks informed damage models for brittle solids." International Journal of Solids and Structures 48, no. 10 (May 2011): 1560–71. http://dx.doi.org/10.1016/j.ijsolstr.2011.02.001.

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31

Rao, Parthib, and Laura Schaefer. "Lattice Boltzmann models for micro-tomographic pore-spaces." Computers & Fluids 193 (October 2019): 104294. http://dx.doi.org/10.1016/j.compfluid.2019.104294.

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32

Abid, Fatma, Khalil Dammak, Abdelkhalak El Hami, Tarek Merzouki, Hassen Trabelsi, Lassaad Walha, and Mohamed Haddar. "Surrogate models for uncertainty analysis of micro-actuator." Microsystem Technologies 26, no. 8 (March 13, 2020): 2589–600. http://dx.doi.org/10.1007/s00542-020-04799-5.

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33

Rodríguez, J. Apolinar Muñoz. "Micro-Scale Spherical and Cylindrical Surface Modeling via Metaheuristic Algorithms and Micro Laser Line Projection." Algorithms 15, no. 5 (April 24, 2022): 145. http://dx.doi.org/10.3390/a15050145.

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With the increasing micro-scale manufacturing industry, the micro-scale spherical and cylindrical surface modeling has become an important factor in the manufacturing process. Thus, the micro-scale manufacturing processes require efficient micro-scale spherical and cylindrical models to achieve accurate assembly. Therefore, it is necessary to implement models to represent micro-scale spherical and cylindrical surfaces. This study addresses metaheuristic algorithms based on micro laser line projection to perform micro-scale spherical and cylindrical surface modeling. In this technique, the micro-scale surface is recovered by an optical microscope system, which computes the surface coordinates via micro laser line projection. From the surface coordinates, a genetic algorithm determines the parameters of the mathematical models to represent the spherical and cylindrical surfaces. The genetic algorithm performs exploration and exploitation in the search space to optimize the models’ mathematical parameters. The search space is constructed via surface data to provide the optimal parameters, which determine the spherical and cylindrical surface models. The proposed technique improves the fitting accuracy of the micro-scale spherical and cylindrical surface modeling performed via optical microscope systems. This contribution is elucidated by a discussion about the model fitting between the genetic algorithms based on micro laser line projection and the optical microscope systems.
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34

Ali, M. Y., A. Sabur, S. R. Ya’akub, A. D. A. Hamid, A. R. Alao, and R. Singh. "Micro-electro discharge machining (Micro-EDM) models for conductive and nonconductive materials: A review." IOP Conference Series: Materials Science and Engineering 1173, no. 1 (August 1, 2021): 012063. http://dx.doi.org/10.1088/1757-899x/1173/1/012063.

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35

Mombelli, Andrea. "In Vitro Models of Biological Responses to Implant Microbiological Models." Advances in Dental Research 13, no. 1 (June 1999): 67–72. http://dx.doi.org/10.1177/08959374990130011701.

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To study the etiology and explore possibilities for the therapy of implant-associated infections, investigators have developed and utilized various in vitro models. Major contributions have come from the non-oral medical field, where device-related infections can create life-threatening situations. Microbiological models may include (i) models to study the reaction of micro-organisms to the presence of implants, (ii) models to study the reaction of implant-associated micro-organisms to antimicrobial agents, and (iii) models to study the reaction of the host tissues to the presence of implants contaminated with micro-organisms. In evaluating the potential usefulness of these models for research in oral implantology, one must consider common features as well as important differences between implanted medical devices and oral implants. Although infections associated with implantable medical devices and oral peri-implant infections share a remarkable number of common features, there are also important differences that need attention when findings from in vitro experiments are extrapolated to clinical relevance.
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36

Tang, Shengjin, Xiaosong Guo, Xiaoyan Sun, Haijian Xue, and Zhaofa Zhou. "Unavailability Analysis fork-out-of-n:G Systems with Multiple Failure Modes Based on Micro-Markov Models." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/740936.

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Markov models are commonly used for unavailability analysis of redundant systems. However, due to the exploding states of Markov models for redundant systems, the states need to be merged to simplify the computation, which is called micro-Markov models. However, how to derive the failure rates and repair rates of the newly developed micro-Markov models has not been studied thoroughly. Therefore, this paper proposes detailed explanations and rules to derive the static unavailability by the micro-Markov models for thek-out-of-n:G systems with multiple failure modes. Firstly, two properties about applying the Markov models to the repairable system with independent multiple failure modes are presented. Based on these two properties, two rules are proposed for implementing the micro-Markov models. The micro-Markov models provide the exact same results for the repairablek-out-of-n:G system with multiple independent failure modes and repair mechanisms and approximate results for systems with multiple hybrid failure modes. A case study of safety integrity verification for safety instrumented systems is provided to illustrate the application of the proposed method. The conceptual comparison and numerical examples demonstrate the reasonability and usefulness of the proposed micro-Markov models.
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37

Kedar, Orit, and W. Phillips Shively. "Introduction to the Special Issue." Political Analysis 13, no. 4 (2005): 297–300. http://dx.doi.org/10.1093/pan/mpi027.

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The use of multilevel models—models in which lower-level (“micro”) units are nested within higher-level (“macro”) units—has blossomed recently in political science. Possible relationships in such models include macro variables influencing macro variables; micro variables influencing micro variables; macro variables influencing micro variables, and vice versa; and often most interestingly, micro-micro relationships varying interactively with macro variables. Most work in political science has drawn on the useful introductions of Raudenbush and Bryk (2002), Western (1998), and Steenbergen and Jones (2002). We refer readers to good general introductions/reviews of multi-level modeling in the articles in this issue by Bowers and Drake and by Franzese.
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38

Isaev, Alexander, Ramil Khamzin, Artem Ershov, and Marco Leonesio. "Mathematical Models of the Geometry of Micro Milling Cutters." EPJ Web of Conferences 248 (2021): 04003. http://dx.doi.org/10.1051/epjconf/202124804003.

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Micromachining is an up-to-date technology widely used in different advanced areas like electronics, aerospace and medical industries. For manufacturing components with highest precision and lowest surface roughness, small-sized end mills with working diameter of less than 1 mm are often used. In this paper, in order to determine the functional relationships between structural strength, cutting properties and geometry of small-sized cutting tools, the mathematical models of working part of micro milling cutters were derived.
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39

Arabi, U. "Micro Finance Initiatives (Models) in India: A Performance Appraisal." SEDME (Small Enterprises Development, Management & Extension Journal): A worldwide window on MSME Studies 36, no. 4 (December 2009): 71–95. http://dx.doi.org/10.1177/0970846420090406.

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40

Asiedu Asante, Bismark, and Hiroki Imamura. "Speech Recognition and Speech Synthesis Models for Micro Devices." ITM Web of Conferences 27 (2019): 05001. http://dx.doi.org/10.1051/itmconf/20192705001.

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With the advent and breakthrough of interaction between humans and electronic devices using speech in communication, we have seen a lot of applications using speech recognition and speech synthesis technology. There are some limitations we have identified to these applications. Availability of a lot of resources and internet connectivity have made it possible in making case but with limited resources it is quite difficult to achieve this feat. As a result, it limits the application of the technology into micro devices and deploying them into areas where there are no internet connectivity. In this article, we developed a smaller Deep Neural Network models for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) for communication on micro devices such as Raspberry Pi. We tested and evaluated the models of the system. The accuracy and the performance of the models to be implemented on micro devices shows that they are good for application development in micro devices.
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41

Aifantis, E. C. "Gradient Deformation Models at Nano, Micro, and Macro Scales." Journal of Engineering Materials and Technology 121, no. 2 (April 1, 1999): 189–202. http://dx.doi.org/10.1115/1.2812366.

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Various deformation models incorporating higher-order gradients are discussed and their implications are considered in a variety of problems ranging from the determination of the size of dislocation cores or elastic dislocation interaction to the determination of wavelengths of dislocation patterns or heterogeneous dislocation distributions and the determination of the structure of solid interfaces and of localized strain zones during adiabatic shear deformation. Different scales are involved in each one of these problems: the nanoscale for single dislocations, the microscale for dislocation patterning, and the macroscale for adiabatic shear banding. Accordingly, different gradient models apply for each case, different types of gradient terms are involved and different expressions of the gradient coefficients are assumed.
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42

Schatzmann, Michael, and Rex Britter. "Quality assurance and improvement of micro-scale meteorological models." International Journal of Environment and Pollution 44, no. 1/2/3/4 (2011): 139. http://dx.doi.org/10.1504/ijep.2011.038412.

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43

Jenkins-Smith, Hank C., Carol L. Silva, and Richard W. Waterman. "Micro- and Macrolevel Models of the Presidential Expectations Gap." Journal of Politics 67, no. 3 (August 2005): 690–715. http://dx.doi.org/10.1111/j.1468-2508.2005.00335.x.

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44

Tabak, Ahmet Fatih, and Serhat Yesilyurt. "Improved Kinematic Models for Two-Link Helical Micro/Nanoswimmers." IEEE Transactions on Robotics 30, no. 1 (February 2014): 14–25. http://dx.doi.org/10.1109/tro.2013.2281551.

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45

Moulin, Gaid, François Goudail, Pierre Chavel, and Dengfeng Kuang. "Heuristic models for diffraction by some simple micro-objects." Journal of the Optical Society of America A 26, no. 4 (March 12, 2009): 767. http://dx.doi.org/10.1364/josaa.26.000767.

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46

Hassan, Tarek M. "Macro and micro models for large scale engineering processes." International Journal of Computer Applications in Technology 18, no. 1/2/3/4 (2003): 189. http://dx.doi.org/10.1504/ijcat.2003.002137.

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47

Gralla, Phil, Iwona Piotrowska-Kurczewski, Daniel Rippel, Michael Lütjen, and Peter Maaß. "Inverting Prediction Models in Micro Production for Process Design." MATEC Web of Conferences 190 (2018): 15007. http://dx.doi.org/10.1051/matecconf/201819015007.

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Databased prediction models are used to estimate a possible outcome for previously unknown production parameters. These forward models enable to test new production designs and parameters virtually before applying them in the real world. Cause-effect networks are one way to generate such a prediction model. Multiple inputs and stages are being connected to one large prediction model. The functional behaviour and correlation of inputs as well as outputs is obtained through data based learning. In general, these models are non-linear and not invertible, especially for micro cold forming processes. While already being useful in process design, such models have their highest impact if inverted to find process parameters for a given output. Combining methods from the mathematical field of inverse problems as well as machine learning, a generalized inverse can be approximated. This allows finding process parameters for a given output without inverting the model directly but still using inherit information of the forward model. In this work, Tikhonov functionals are used to perform a parameter identification. The classical approach is altered by changing the discrepancy term to incorporate tolerances. Thereby, small deviations of a certain pattern are being neglected and the parameter finding process is being stabilized. In addition, different types of regularization are taken into consideration. Besides theoretical aspects of this method, examples are provided to demonstrate advantages and boundaries of an application for the process design in micro cold forming processes.
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48

Lee, Vanessa K., John M. David, and Michael J. Huerkamp. "Micro- and Macroenvironmental Conditions and Stability of Terrestrial Models." ILAR Journal 60, no. 2 (2019): 120–40. http://dx.doi.org/10.1093/ilar/ilaa013.

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Abstract Environmental variables can have profound effects on the biological responses of research animals and the outcomes of experiments dependent on them. Some of these influences are both predictable and unpredictable in effect, many are challenging to standardize, and all are influenced by the planning and conduct of experiments and the design and operation of the vivarium. Others are not yet known. Within the immediate environment where the research animal resides, in the vivarium and in transit, the most notable of these factors are ambient temperature, relative humidity, gaseous pollutant by-products of animal metabolism and physiology, dust and particulates, barometric pressure, electromagnetic fields, and illumination. Ambient temperatures in the animal housing environment, in particular those experienced by rodents below the thermoneutral zone, may introduce degrees of stress and thermoregulatory compensative responses that may complicate or invalidate study measurements across a broad array of disciplines. Other factors may have more subtle and specific effects. It is incumbent on scientists designing and executing experiments and staff responsible for animal husbandry to be aware of, understand, measure, systematically record, control, and account for the impact of these factors on sensitive animal model systems to ensure the quality and reproducibility of scientific studies.
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49

Anders Klevmarken, N. "Statistical inference in micro-simulation models: incorporating external information." Mathematics and Computers in Simulation 59, no. 1-3 (May 2002): 255–65. http://dx.doi.org/10.1016/s0378-4754(01)00413-x.

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50

Tan, Ping, and Liyong Tong. "Micro-electromechanics models for piezoelectric-fiber-reinforced composite materials." Composites Science and Technology 61, no. 5 (April 2001): 759–69. http://dx.doi.org/10.1016/s0266-3538(01)00014-8.

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