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Relevant bibliographies by topics / Estimation de l'horizon mobile

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Academic literature on the topic 'Estimation de l'horizon mobile'

Author: Grafiati

Published: 14 September 2024

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Journal articles on the topic "Estimation de l'horizon mobile"

1

THIVOLLE-CAZAT (Alain) and PIGNARD (Gérôme). "Estimation du volume de bois résineux disponible en France à l'horizon 2010." Revue Forestière Française, no. 3-4 (2001): 317. http://dx.doi.org/10.4267/2042/5243.

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2

Kumar, Shailesh, and Anant R. Koppar. "Software Estimation Framework for Mobile Application Projects." International Journal of Productivity Management and Assessment Technologies 7, no. 2 (2019): 26–40. http://dx.doi.org/10.4018/ijpmat.2019070102.

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As mobile devices are becoming the primary access channels for information, the authors need to have accurate effort estimation model for mobile application projects. In this paper the authors discuss “Mobile application estimation framework” that was designed based on 14 mobile application projects and was validated against 5 mobile application projects. In this paper the authors discuss the estimation framework for both native/hybrid mobile application projects and mobile web application projects. The proposed “Mobile application estimation framework” provides comprehensive coverage for various factors involved in mobile estimation such as layer-wise components, horizontal components and others. The estimation framework also considers the cost drivers and is used as effort adjustment factor. The proposed mobile application estimation framework achieved the MMRE of 0.207 with pred (0.3) of 80%.

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3

Kim, Cheong-Hwan, Dae-Seung Ban, and Yong-Hwan Lee. "Channel estimation in mobile WiMAX systems." International Conference on Electrical Engineering 6, no. 6 (2008): 1–13. http://dx.doi.org/10.21608/iceeng.2008.34233.

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4

Rzeszucinski, Pawel, Daniel Lewandowski, and Cajetan T. Pinto. "Mobile device-based shaft speed estimation." Measurement 96 (January 2017): 52–57. http://dx.doi.org/10.1016/j.measurement.2016.10.005.

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5

McGuire, M., K. N. Plataniotis, and A. N. Venetsanopoulos. "Robust estimation of mobile terminal position." Electronics Letters 36, no. 16 (2000): 1426. http://dx.doi.org/10.1049/el:20000960.

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6

Kaur, Anureet, and Kulwant Kaur. "Effort Estimation in Traditional and Agile Mobile Application Development & Testing." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 3 (2018): 1265. http://dx.doi.org/10.11591/ijeecs.v12.i3.pp1265-1272.

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Smartphones<em>/</em>mobile devices are enduring all the aspects of human life. With the significant increase in demand for applications running on smartphones/mobile devices, developers and testers are anticipated to deliver high quality, on time and within budget applications. The estimation of development and testing provides a baseline and act as a tracking gear for stakeholders and developers. There are various approaches for estimation of traditional software development. But mobile applications are considered different from traditional software such as from those running on desktop, laptop or on the web. Many traditional estimation techniques used for these software are adapted to mobile domain. With agile software development (ASD) methodology, the scenario of development and estimation has changed drastically and so as mobile app development and estimation. This paper provides a Systematic Literature Review (SLR) on traditional estimation techniques and agile estimation techniques applied in mobile software/application. Also, effort attributes and accuracy parameters for estimation in mobile apps are presented. However, to date, there are very fewer studies done on the mobile application estimation domain using agile methodology.

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7

Fernandes, Thiago Soares, Álvaro Freitas Moreira, and Érika Cota. "EPE-Mobile-A framework for early performance estimation of mobile applications." Software: Practice and Experience 48, no. 1 (2017): 85–104. http://dx.doi.org/10.1002/spe.2518.

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8

Zajic, Alenka G. "Estimation of Mobile Velocities and Direction of Movement in Mobile-to-Mobile Wireless Fading Channels." IEEE Transactions on Vehicular Technology 61, no. 1 (2012): 130–39. http://dx.doi.org/10.1109/tvt.2011.2175410.

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9

KIM, SUNGBOK, and SANGHYUP LEE. "ROBUST MOBILE ROBOT VELOCITY ESTIMATION USING A POLYGONAL ARRAY OF OPTICAL MICE." International Journal of Information Acquisition 05, no. 04 (2008): 321–30. http://dx.doi.org/10.1142/s0219878908001715.

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This paper presents the robust velocity estimation of a mobile robot using a polygonal array of optical mice that are installed at the bottom of the mobile robot. First, the velocity kinematics from a mobile robot to an array of optical mice is derived, from which the least squares estimation of a mobile robot velocity is obtained. Second, the least squares mobile robot velocity estimation is shown to be robust against measurement noises and partial malfunctions of optical mice. Third, in the presence of installation error, a practical method for optical mouse position calibration is devised. Finally, some experimental results are given to demonstrate the validity and performance of the proposed mobile robot velocity estimation.

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10

Röhrig, Christof, and Frank Künemund. "WLAN based Pose Estimation for Mobile Robots." IFAC Proceedings Volumes 41, no. 2 (2008): 10433–38. http://dx.doi.org/10.3182/20080706-5-kr-1001.01768.

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