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Journal articles on the topic 'Dynamic sensing'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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1

Braggins, Don. "Dynamic sensing." Sensor Review 24, no. 1 (2004): 30–32. http://dx.doi.org/10.1108/02602280410515789.

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2

HATANAKA, HIROSHI. "Dynamic pressure sensing." Journal of the Japan Society for Precision Engineering 52, no. 4 (1986): 615–18. http://dx.doi.org/10.2493/jjspe.52.615.

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3

Baden-Fuller, Charles, and David J. Teece. "Market sensing, dynamic capability, and competitive dynamics." Industrial Marketing Management 89 (August 2020): 105–6. http://dx.doi.org/10.1016/j.indmarman.2019.11.008.

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4

Yu, Francis T. S., Kun Pan, Dazun Zhao, and Paul B. Ruffin. "Dynamic fiber specklegram sensing." Applied Optics 34, no. 4 (1995): 622. http://dx.doi.org/10.1364/ao.34.000622.

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5

Talaie, Afshad, Ji-Yoon Lee, Kimihiro Adachi, Takahisa Taguchi, and Jose Romagnoli. "Dynamic polymeric electrodes, dynamic computer modeling and dynamic electrochemical sensing." Journal of Electroanalytical Chemistry 468, no. 1 (1999): 19–25. http://dx.doi.org/10.1016/s0022-0728(99)00091-1.

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6

J. V. Stafford and J. G. Hendrick. "Dynamic Sensing of Soil Pans." Transactions of the ASAE 31, no. 1 (1988): 0009–13. http://dx.doi.org/10.13031/2013.30656.

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7

Gamper, Urs, Peter Boesiger, and Sebastian Kozerke. "Compressed sensing in dynamic MRI." Magnetic Resonance in Medicine 59, no. 2 (2008): 365–73. http://dx.doi.org/10.1002/mrm.21477.

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8

Lingala, S. G., and M. Jacob. "Blind Compressive Sensing Dynamic MRI." IEEE Transactions on Medical Imaging 32, no. 6 (2013): 1132–45. http://dx.doi.org/10.1109/tmi.2013.2255133.

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9

Gilkerson, Robert. "A Disturbance in the Force: Cellular Stress Sensing by the Mitochondrial Network." Antioxidants 7, no. 10 (2018): 126. http://dx.doi.org/10.3390/antiox7100126.

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As a highly dynamic organellar network, mitochondria are maintained as an organellar network by delicately balancing fission and fusion pathways. This homeostatic balance of organellar dynamics is increasingly revealed to play an integral role in sensing cellular stress stimuli. Mitochondrial fission/fusion balance is highly sensitive to perturbations such as loss of bioenergetic function, oxidative stress, and other stimuli, with mechanistic contribution to subsequent cell-wide cascades including inflammation, autophagy, and apoptosis. The overlapping activity with m-AAA protease 1 (OMA1) met

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10

Villalon-Turrubiates, I. E. "DYNAMICAL PREDICTION TECHNIQUE FOR GEOSIMULATION USING MULTISPECTRAL REMOTE SENSING DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4 (September 19, 2018): 213–19. http://dx.doi.org/10.5194/isprs-annals-iv-4-213-2018.

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<p><strong>Abstract.</strong> The analysis of dynamical models for prediction and geosimulation using the information extracted from a geographical region processed from the data provided by multispectral remote sensing systems provides useful information for urban planning and resource management. However, several topics of interest on this particular matter are still to be properly studied. Using the remote sensing data that has been extracted from multispectral images from a particular geographic region in discrete time, its dynamic study is performed in both, spatial reso

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11

Astaiza-Hoyos, Evelio, Pablo Jojoa, and Héctor Bermúdez. "Local Wideband Spectrum Sensing Dynamic Algorithm Based on Compressive Sensing." International Journal of Engineering and Technology 8, no. 5 (2016): 2221–33. http://dx.doi.org/10.21817/ijet/2016/v8i5/160805074.

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12

Lee, Tae-Gyu, Seong-Hoon Lee, and Hye-Young Kim. "Dynamic Configuration Method of Process Design in Bio-sensing Information Computing System." International Journal of Bio-Science and Bio-Technology 5, no. 6 (2013): 147–56. http://dx.doi.org/10.14257/ijbsbt.2013.5.6.15.

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13

Kaneko, Makoto. "Super High Speed Dynamic Active Sensing." Journal of the Robotics Society of Japan 26, no. 7 (2008): 752. http://dx.doi.org/10.7210/jrsj.26.752.

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14

Casciati, Fabio, Sara Casciati, and Li Jun Wu. "Vision-Based Sensing in Dynamic Tests." Key Engineering Materials 569-570 (July 2013): 767–74. http://dx.doi.org/10.4028/www.scientific.net/kem.569-570.767.

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The availability of a suitable data acquisition sensor network is a key implementation issue to link models with real world structures. Non-contact displacement sensors should be preferred since they do not change the system properties. A two-dimensional vision-based displacement measurement sensor is the focus of this contribution. In particular, the perspective distortion introduced by the angle between the optic axis of the camera and the normal to the plane in which the structural system deforms is considered. A two-dimensional affine transformation is utilized to eliminate the distortion

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15

Odejide, Olusegun. "Dynamic Spectrum Detection Via Compressive Sensing." International journal of Computer Networks & Communications 4, no. 2 (2012): 101–16. http://dx.doi.org/10.5121/ijcnc.2012.4207.

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16

Lee, Juong-Sik, and Baik Hoh. "Dynamic pricing incentive for participatory sensing." Pervasive and Mobile Computing 6, no. 6 (2010): 693–708. http://dx.doi.org/10.1016/j.pmcj.2010.08.006.

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17

Dürig, U. "Interaction sensing in dynamic force microscopy." New Journal of Physics 2 (March 14, 2000): 5. http://dx.doi.org/10.1088/1367-2630/2/1/005.

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18

Kaneko, Makoto. "Super-High-Speed Dynamic Active Sensing." Advanced Robotics 23, no. 11 (2009): 1505–6. http://dx.doi.org/10.1163/016918609x12469678285679.

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19

Sahoo, Jagruti, Soumaya Cherkaoui, Abdelhakim Hafid, and Pratap Kumar Sahu. "Dynamic Hierarchical Aggregation for Vehicular Sensing." IEEE Transactions on Intelligent Transportation Systems 18, no. 9 (2017): 2539–56. http://dx.doi.org/10.1109/tits.2017.2650991.

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20

L. Brunton, Steven, Joshua L. Proctor, Jonathan H. Tu, and J. Nathan Kutz. "Compressed sensing and dynamic mode decomposition." Journal of Computational Dynamics 2, no. 2 (2015): 165–91. http://dx.doi.org/10.3934/jcd.2015002.

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21

Sentic, Milica, Stéphane Arbault, Bertrand Goudeau, et al. "Electrochemiluminescent swimmers for dynamic enzymatic sensing." Chem. Commun. 50, no. 71 (2014): 10202–5. http://dx.doi.org/10.1039/c4cc04105d.

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22

Ueno, N., M. M. Svinin, and M. Kaneko. "Dynamic contact sensing by flexible beam." IEEE/ASME Transactions on Mechatronics 3, no. 4 (1998): 254–64. http://dx.doi.org/10.1109/3516.736160.

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23

Ho, Siu Chun Michael, Liang Ren, Hongnan Li, and Gangbing Song. "Dynamic fiber Bragg grating sensing method." Smart Materials and Structures 25, no. 2 (2016): 025028. http://dx.doi.org/10.1088/0964-1726/25/2/025028.

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24

Camley, Brian A. "Emergent Shape Sensing of Dynamic Membranes." Biophysical Journal 116, no. 3 (2019): 216a—217a. http://dx.doi.org/10.1016/j.bpj.2018.11.1195.

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25

Zhou, Yin, Lianshan Yan, Haijun He, et al. "DWI-Assisted BOTDA for Dynamic Sensing." Journal of Lightwave Technology 39, no. 11 (2021): 3599–606. http://dx.doi.org/10.1109/jlt.2021.3068071.

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26

Sun, J., and H. Xiang. "RESEARCH ON KEY TECHNOLOGY OF MINING REMOTE SENSING DYNAMIC MONITORING INFORMATION SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 893–96. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-893-2017.

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Problems exist in remote sensing dynamic monitoring of mining are expounded, general idea of building remote sensing dynamic monitoring information system is presented, and timely release of service-oriented remote sensing monitoring results is established. Mobile device-based data verification subsystem is developed using mobile GIS, remote sensing dynamic monitoring information system of mining is constructed, and "timely release, fast handling and timely feedback" rapid response mechanism of remote sensing dynamic monitoring is implemented.

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27

Tempelmayr, David, Doris Ehrlinger, Christian Stadlmann, Margarethe Überwimmer, Stefan Mang, and Anna Biedersberger. "The Performance Effect of Dynamic Capabilities in Servitizing Companies." JOURNAL OF INTERNATIONAL BUSINESS RESEARCH AND MARKETING 4, no. 6 (2019): 42–48. http://dx.doi.org/10.18775/jibrm.1849-8558.2015.46.3005.

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As an increasing number of companies operates in international markets characterized by global competition, many traditional manufacturers augment their product offerings with services to gain competitive advantage. As servitization needs change throughout the company, many companies struggle on the transition from a product – to a service centric business model. The dynamic capabilities view analyses capabilities in changing environments and could therefore be an interesting theoretical lens for servitization research. Building on existing case research of dynamic capabilities in a servitizat

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28

He, Huan Huan, Xing Wei Wang, and Min Huang. "A Coalitional Game Based Dynamic Spectrum Sensing Scheme." Applied Mechanics and Materials 556-562 (May 2014): 6094–101. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.6094.

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. In this paper, to help cognitive users conduct fair and efficient spectrum sensing in the heterogeneous wireless environments, a coalitional game based spectrum sensing scheme is proposed. The method of calculating the basic parameters of spectrum sensing is introduced at first, and then the spectrum sensing problem is modeled as a coalitional game with non-transferable utility. A coalition is built with Pareto optimality satisfied, and its procedure is described in details. Simulation results have shown that the proposed scheme is both feasible and effective.

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29

Zhang, Ji, Tie Zhu Zhang, and Lian Jun Cheng. "Dynamic Simulation Research Based on AMESim Load-Sensing Pump." Applied Mechanics and Materials 687-691 (November 2014): 195–200. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.195.

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In this paper, based on the analysis of load-sensing principles, load-sensing pump mathematical model is derived, using the software AMESim to establish the physical model is intuitive, and conducts the simulation research, the dynamic operation curve. Research has shown that: load sensing valve spring stiffness, spool, spool diameter opening shape and quality response to dynamic load sensing pump will have a significant impact, which has a certain reference value for designing and using load sensing pump.

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30

Yin, Yunfei, Liufa Guan, and Chengen Zheng. "An Approach to Dynamic Sensing Data Fusion." Sensors 19, no. 17 (2019): 3668. http://dx.doi.org/10.3390/s19173668.

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For the research and development of sensor systems, the collection and fusion of sensing data is the core. In order to make sensor data acquisition change with the change in environment, a dynamic data acquisition and fusion method based on feedback control is proposed in this paper. According to the sensing data acquisition and fusion model, the optimal acquisition of sensor data is achieved through real-time dynamic judgment of the collected data, decision-making of the next acquisition time interval, and adjustment. This model enables the sensor system to adapt to different environments. An

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31

Ishii, Idaku. "Dynamic Sensing Applications of High-speed Vision." Journal of the Robotics Society of Japan 32, no. 9 (2014): 793–97. http://dx.doi.org/10.7210/jrsj.32.793.

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32

UCHIYAMA, MASARU. "Dynamic force sensing of a robot manipulator." Journal of the Japan Society for Precision Engineering 52, no. 4 (1986): 623–26. http://dx.doi.org/10.2493/jjspe.52.623.

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33

Pournajaf, Layla, Li Xiong, and Vaidy Sunderam. "Dynamic Data Driven Crowd Sensing Task Assignment." Procedia Computer Science 29 (2014): 1314–23. http://dx.doi.org/10.1016/j.procs.2014.05.118.

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34

Gillmer, Steven R., Xiangzhi Yu, Chen Wang, and Jonathan D. Ellis. "Robust high-dynamic-range optical roll sensing." Optics Letters 40, no. 11 (2015): 2497. http://dx.doi.org/10.1364/ol.40.002497.

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35

Grant, D., and R. Pearce. "Dynamic performance of current-sensing power MOSFETs." Electronics Letters 24, no. 18 (1988): 1129. http://dx.doi.org/10.1049/el:19880768.

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36

Hu, Junpeng, Zhen Zuo, Zhiping Huang, and Zhi Dong. "Dynamic Digital Channelizer Based on Spectrum Sensing." PLOS ONE 10, no. 8 (2015): e0136349. http://dx.doi.org/10.1371/journal.pone.0136349.

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37

Rust, David, and David Roundhill. "System and method of dynamic automatic sensing of available dynamic range." Journal of the Acoustical Society of America 115, no. 5 (2004): 1882. http://dx.doi.org/10.1121/1.1757220.

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38

Shinde, Y. S., and H. Kaur Gahir. "Dynamic Pressure Sensing Study Using Photonic Crystal Fiber: Application to Tsunami Sensing." IEEE Photonics Technology Letters 20, no. 4 (2008): 279–81. http://dx.doi.org/10.1109/lpt.2007.913741.

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39

Howe, R. D., and M. R. Cutkosky. "Dynamic tactile sensing: perception of fine surface features with stress rate sensing." IEEE Transactions on Robotics and Automation 9, no. 2 (1993): 140–51. http://dx.doi.org/10.1109/70.238278.

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40

Maijanen, Päivi, and Paavo Ritala. "Dynamics of Dynamic Capabilities: Cross-Level Processes of Sensing, Seizing and Transforming." Academy of Management Proceedings 2018, no. 1 (2018): 12319. http://dx.doi.org/10.5465/ambpp.2018.12319abstract.

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41

Wang, Aosen, Feng Lin, Zhanpeng Jin, and Wenyao Xu. "Ultra-Low Power Dynamic Knob in Adaptive Compressed Sensing Towards Biosignal Dynamics." IEEE Transactions on Biomedical Circuits and Systems 10, no. 3 (2016): 579–92. http://dx.doi.org/10.1109/tbcas.2015.2497304.

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42

Fang, Yanzhuo. "Study on Remote Sensing Dynamic Monitoring of Geological Environment." Remote Sensing 9, no. 2 (2020): 30. http://dx.doi.org/10.18282/rs.v9i2.1106.

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<p>With the continuous development of science and technology, remote sensing technology has become more and more mature and more advanced in our country, and the application of remote sensing technology to the monitoring of geological environment is also an important research problem in continuous improvement in recent years. China has a vast land area, rich mineral resources, strong geological diversity and complex geological environment, and the geological exploration of the origin of mineral resources is a prerequisite for the rationality of mineral development. Therefore, the remote

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43

Lee, Youngseok, Seong Ro Lee, Seungsoo Yoo, Jaewoo Lee, Jeongyoon Shim, and Seok Ho Yoon. "A Cyclostationarity-Based Spectrum Sensing Scheme for Dynamic Traffic Circumstances." Applied Mechanics and Materials 479-480 (December 2013): 778–82. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.778.

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In this paper, we propose a cyclostationarity-based spectrum sensing scheme for dynamic traffic circumstances. First, we model the spectrum sensing problem in dynamic traffic circumstances as a binary hypothesis testing problem where primary users (PUs) might randomly depart or arrive during the sensing period. Then, we develop a generalized likelihood ratio (GLR) and derive a test statistic via the GLR, which is based on the cyclostationarity of the PU signals. Numerical results confirm that the proposed scheme offers a better spectrum sensing performance than the conventional scheme based on

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44

Modaresnezhad, Minoo, and Hamid Nemati. "Participatory Sensing or Sensing of Participation." International Journal of Technology and Human Interaction 16, no. 3 (2020): 124–43. http://dx.doi.org/10.4018/ijthi.2020070108.

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Smart devices have become a basic necessity in this technically advanced era. Many smart device applications, when installed, collect personal data and track users' online behavior for marketing or other purposes. This study aims to explore whether users are aware of related privacy issues and whether their knowledge influences the usage of their apps. Cognate-based views of privacy indicate that privacy concern is dynamic and varies depending on an individual's characteristics and the context. Adopting this view creates the attempt to understand the effect of privacy awareness on user's behav

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45

Bogodistov, Yevgen, André Presse, Oleksandr P. Krupskyi, and Sergii Sardak. "GENDERING DYNAMIC CAPABILITIES IN MICRO FIRMS." Revista de Administração de Empresas 57, no. 3 (2017): 273–82. http://dx.doi.org/10.1590/s0034-759020170308.

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ABSTRACT Gender issues are well-researched in the general management literature, particular in studies on new ventures. Unfortunately, gender issues have been largely ignored in the dynamic capabilities literature. We address this gap by analyzing the effects of gender diversity on dynamic capabilities among micro firms. We consider the gender of managers and personnel in 124 Ukrainian tourism micro firms. We examine how a manager's gender affects the firm's sensing capacities and investigate how it moderates team gender diversity's impact on sensing capacities. We also investigate how personn

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46

SATO, YASUHISA. "Dynamic sensing with bonded strain gages - Application to dynamic testing of materials." Journal of the Japan Society for Precision Engineering 52, no. 4 (1986): 610–14. http://dx.doi.org/10.2493/jjspe.52.610.

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47

Cui, Cuimei, and Dezhi Yang. "Throughput optimization for dual collaborative spectrum sensing with dynamic scheduling." Modern Physics Letters B 31, no. 19-21 (2017): 1740089. http://dx.doi.org/10.1142/s0217984917400899.

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Cognitive radio technology is envisaged to alleviate both spectrum inefficiency and spectrum scarcity problems by exploiting the existing licensed spectrum opportunistically. However, cognitive radio ad hoc networks (CRAHNs) impose unique challenges due to the high dynamic scheduling in the available spectrum, diverse quality of service (QOS) requirements, as well as hidden terminals and shadow fading issues in a harsh radio environment. To solve these problems, this paper proposes a dynamic and variable time-division multiple-access scheduling mechanism (DV-TDMA) incorporated with dual collab

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48

DONG Li-li, 董丽丽, 曹旗磊 CAO Qi-lei, 赵明 ZHAO Ming, 吴厚德 WU Hou-de, and 许文海 XU Wen-hai. "Dynamic Clamping Design of Space Remote Sensing Cameras." ACTA PHOTONICA SINICA 46, no. 1 (2017): 111002. http://dx.doi.org/10.3788/gzxb20174601.0111002.

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49

Zhuang Jia-Yan, Chen Qian, He Wei-Ji, and Mao Tian-Yi. "Imaging through dynamic scattering media with compressed sensing." Acta Physica Sinica 65, no. 4 (2016): 040501. http://dx.doi.org/10.7498/aps.65.040501.

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50

Kullaa, Jyrki. "Virtual sensing of structural vibrations using dynamic substructuring." Mechanical Systems and Signal Processing 79 (October 2016): 203–24. http://dx.doi.org/10.1016/j.ymssp.2016.02.045.

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