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Journal articles on the topic 'Target control'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Dada, Olaniyi, Modupe Aderemi Ogundapo, and Ishola Abel Oladeji. "Target Costing: A Strategic Management Accounting Tool for Enhancing Institutional Competitiveness." Journal of Forensic accounting & Fraud Investigation (JFAFI) 10, Issue 1, January - June, 2025 (2024): 107–22. https://doi.org/10.5281/zenodo.15438082.

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The study examined target costing as a strategic management accounting tool for enhancing institutional competitiveness. In the context of financial targets and target control, the study investigated the awareness and application of target costing among top performing and highly ranked Nigerian Private Universities.  The sample frame is accredited private universities. To ensure regional diversity for the scope of the study, universities were selected from the southwest, North-Central and North-East. The study adopted purposive sampling techniques to arrive at top

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2

Li, Guoqi, Pei Tang, Xumin Chen, et al. "Target control and expandable target control of complex networks." Journal of the Franklin Institute 357, no. 6 (2020): 3541–64. http://dx.doi.org/10.1016/j.jfranklin.2019.11.064.

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3

Pearson, R. K., and B. A. Ogunnaike. "Target-Set Control." IFAC Proceedings Volumes 37, no. 1 (2004): 373–78. http://dx.doi.org/10.1016/s1474-6670(17)38760-8.

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4

Doyen, L., and M. Quincampoix. "Multi-Target Control Problems." Journal of Optimization Theory and Applications 93, no. 1 (1997): 121–39. http://dx.doi.org/10.1023/a:1022601901895.

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5

Dattani, Justine, Jack C. H. Blake, and Frank M. Hilker. "Target-oriented chaos control." Physics Letters A 375, no. 45 (2011): 3986–92. http://dx.doi.org/10.1016/j.physleta.2011.08.066.

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6

Mou, Shaoshuai, Ming Cao, and A. Stephen Morse. "Target-point formation control." Automatica 61 (November 2015): 113–18. http://dx.doi.org/10.1016/j.automatica.2015.08.004.

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7

Wang, Wenchu, Defu Cai, and Xueming Liu. "Control capacity and bimodality in target control." Europhysics Letters 139, no. 5 (2022): 51004. http://dx.doi.org/10.1209/0295-5075/ac8a11.

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Abstract Controlling large networks is a fundamental problem and a great challenge in network science. Typically, full control is not necessary and infeasible. In many cases, only a preselected subset of nodes is required to be controlled, which is the target control problem. Each node does not participate in controlling the target set with equal probability, prompting us to quantify their contributions for target control. Here we develop a random sampling method to estimate the likelihood of each node participating as a driver node in target control configurations and demonstrate the unbiased

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8

Jeon, In-Soo, and Mark Karpenko. "Off-Target Look Angle Control Guidance Law for Moving Targets." Journal of Guidance, Control, and Dynamics 42, no. 11 (2019): 2432–42. http://dx.doi.org/10.2514/1.g004278.

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9

Wang, Jifang, Shengtao Geng, QingE Wu, Wei Wang, and Tianshe Yang. "A Target Control Method Through Eliminating Fuzziness of Target." Journal of Computational and Theoretical Nanoscience 13, no. 11 (2016): 8658–65. http://dx.doi.org/10.1166/jctn.2016.6027.

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10

Stiling, Peter. "Biological Control not on Target." Biological Invasions 6, no. 2 (2004): 151–59. http://dx.doi.org/10.1023/b:binv.0000022130.54793.b7.

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11

Crunkhorn, Sarah. "New target for appetite control." Nature Reviews Drug Discovery 11, no. 8 (2012): 600–601. http://dx.doi.org/10.1038/nrd3803.

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12

Trontis, Anastasios, Hao Xia, Yan Pang, and Michael P. Spathopoulos. "TARGET CONTROL FOR HYBRID SYSTEMS." IFAC Proceedings Volumes 35, no. 1 (2002): 217–22. http://dx.doi.org/10.3182/20020721-6-es-1901.00524.

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13

SCHNEIDER, MARY ELLEN. "New Rules Target Infection Control." Hospitalist News 1, no. 4 (2008): 1–4. http://dx.doi.org/10.1016/s1875-9122(08)70095-6.

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14

Cordo, Paul J., and Martha Flanders. "Sensory control of target acquisition." Trends in Neurosciences 12, no. 3 (1989): 110–17. http://dx.doi.org/10.1016/0166-2236(89)90167-7.

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15

Epstein, R. H. "RESTARTING PROPOFOL TARGET CONTROL INFUSIONS." Anesthesia & Analgesia 88, Supplement (1999): 327S. http://dx.doi.org/10.1097/00000539-199902001-00324.

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16

HELLMAN, RICHARD. "Glycemic Control Target: Patient Safety." Clinical Endocrinology News 4, no. 6 (2009): 7. https://doi.org/10.1016/s1558-0164(09)70168-3.

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17

TASHIRO, Tsutomu. "G1010103 Vehicle Steering Control for Target Parking Position by Predictive Control without Target Trajectory." Proceedings of Mechanical Engineering Congress, Japan 2014 (2014): _G1010103——_G1010103—. http://dx.doi.org/10.1299/jsmemecj.2014._g1010103-.

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18

Sullivan, M., S. W. Butler, J. Hirsch, and C. J. Wang. "A control-to-target architecture for process control." IEEE Transactions on Semiconductor Manufacturing 7, no. 2 (1994): 134–48. http://dx.doi.org/10.1109/66.286850.

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19

Jäger, E., H. Brand, Ch E. Düllmann, et al. "High intensity target wheel at TASCA: target wheel control system and target monitoring." Journal of Radioanalytical and Nuclear Chemistry 299, no. 2 (2013): 1073–79. http://dx.doi.org/10.1007/s10967-013-2645-1.

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20

Hou, Libing, Jihong Zhu, Minchi Kuang, and Heng Shi. "Impact Angle Control Guidance to Intercept Moving Targets by Virtual Target Technique." International Journal of Aerospace Engineering 2021 (December 21, 2021): 1–12. http://dx.doi.org/10.1155/2021/7210808.

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To solve the problem regarding the impact angle of the missile, this paper proposes a novel guidance law, which can control the missile to hit the target at the desired angle. The key of the guidance law is selecting a moving point on the collision line as the virtual target, and the tactical requirements can be fulfilled by the missile directly pursuing the virtual target. The Lyapunov stable theory is used to prove the convergence of the proposed guidance law. The guidance command is generated by a PID controller to make the missile towards the virtual target. The proposed guidance law makes

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21

Testé, Benoit. "Control Beliefs and Dehumanization." Swiss Journal of Psychology 76, no. 2 (2017): 81–86. http://dx.doi.org/10.1024/1421-0185/a000194.

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Abstract. The present research examined the impact of the expression of internal versus external control beliefs on attributions of humanness. Building on previous findings on the cultural norm of internality and the dehumanization of others in social perceptions, we hypothesized that, in a Western society, an individual’s expression of an internal locus of control (i.e., internality) results in a greater degree of humanization of that individual by others than an individual’s expression of an external locus of control (i.e., externality). Two studies examined the effect of a target’s expressi

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22

Barrett, Doug J. K., and Oliver Zobay. "Attentional Control via Parallel Target-Templates in Dual-Target Search." PLoS ONE 9, no. 1 (2014): e86848. http://dx.doi.org/10.1371/journal.pone.0086848.

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23

Li, Chao, Gang Huang, Zhongyang Hao, and Cheng Liu. "A Motion Control Simulation Based on Predictive Model." Journal of Physics: Conference Series 2333, no. 1 (2022): 012012. http://dx.doi.org/10.1088/1742-6596/2333/1/012012.

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Abstract How to improve target tracking efficiency, how to track targets with different motion forms, and establish target motion models are the main research directions. This paper expounds a motion control algorithm based on the prediction model. By establishing the motion equation and prediction model of the target, setting the estimated parameters, optimizing the initial value setting, and predicting the motion state of the target, the simulation analysis based on MATLAB is completed. The simulation results show that the motion control algorithm based on the prediction model has good robus

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24

Sun, Rong Chun, and Xue Song. "Control System of Moving Target Simulator." Advanced Materials Research 442 (January 2012): 488–92. http://dx.doi.org/10.4028/www.scientific.net/amr.442.488.

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To test the accuracy of image motion compensation of space camera, the moving target simulator was developed according to the principle of relative motion. As the core controller, PIC microcontroller controls DC motor to drive photoetching turntable rotating to simulate the relative linear velocity between ground target and aircraft, and the rotation motion is divided into uniform velocity rotation and sinusoidal velocity rotation. Furthermore, the simulation of drift angle of aircraft was realized by controlling stepper motor to drive the photoetching turntable deflecting, and the deflection

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25

DESAI, T., and H. C. PANT. "Control of Rayleigh–Taylor instabilities in laser accelerated seeded targets." Laser and Particle Beams 18, no. 1 (2000): 119–28. http://dx.doi.org/10.1017/s0263034600181145.

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It is important to ameliorate the early time imprinting of nonuniformities due to laser radiation or target shell surface in an inertial confinement fusion (ICF) scheme. However, they will not prevent the instabilities which originate at the ablation surface due to acceleration of high density plasma by low density plasma. One of the methods discussed here is to combat the growth of instabilities at the ablation surface. The present work is aimed to control growth of hydrodynamic instability in laser irradiated target at moderate intensities. Laser (λ = 1.06 μm) radiation was focused on the pl

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26

Paterson, Iain D., Martin P. Hill, Kim Canavan, and Paul O. Downey. "Prioritisation of targets for weed biological control II: the South African Biological Control Target Selection system." Biocontrol Science and Technology 31, no. 6 (2021): 566–83. http://dx.doi.org/10.1080/09583157.2021.1918637.

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27

Meng, Tao, Gaopeng Duan, Aming Li, and Long Wang. "Control energy scaling for target control of complex networks." Chaos, Solitons & Fractals 167 (February 2023): 112986. http://dx.doi.org/10.1016/j.chaos.2022.112986.

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28

Yang, Zhaohua, Wen Jiang, Xia Liu, and Zhenqiang Qi. "Predictive control of aircraft control systems for maneuverable target." Journal of the Franklin Institute 355, no. 18 (2018): 9036–52. http://dx.doi.org/10.1016/j.jfranklin.2016.10.001.

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29

Yang, Pey-Yu, Feng-Ing Yao, and Rong-Ju Cherng. "P-43 EFFECT OF TARGET DISTANCE ON ANTICIPATORY POSTURAL CONTROL IN STANDING." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2007.3 (2007): S131. http://dx.doi.org/10.1299/jsmeapbio.2007.3.s131.

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30

Hawkins, Bradford A. "Non-target Effects of Biological Control." Ecology 81, no. 11 (2000): 3260–61. http://dx.doi.org/10.1890/0012-9658(2000)081[3260:nteobc]2.0.co;2.

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31

Wang, Na, Jinguo Wang, and Dechuan Liu. "Intelligent Control and Target-controlled Infusion." MATEC Web of Conferences 267 (2019): 01003. http://dx.doi.org/10.1051/matecconf/201926701003.

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With the development of science and technology, intelligent control system has been used more and more widely. Closed-loop target-controlled infusion system is a typical example. This great combination of medicine and intelligent control system, especially in the field of anesthesia, solves many clinical problems. This article mainly introduces some typical examples of closed-loop target-controlled infusion system.

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32

Bouchard, Bruno, Romuald Elie, and Cyril Imbert. "Optimal Control under Stochastic Target Constraints." SIAM Journal on Control and Optimization 48, no. 5 (2010): 3501–31. http://dx.doi.org/10.1137/090757629.

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33

Trontis, Anastasios, and Michael P. Spathopoulos. "Supervisory target control for hybrid systems." International Journal of Control 76, no. 11 (2003): 1142–58. http://dx.doi.org/10.1080/0020717031000123328.

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34

Chua, Romeo, and Digby Elliott. "Visual control of target-directed movements." Behavioral and Brain Sciences 20, no. 2 (1997): 304–6. http://dx.doi.org/10.1017/s0140525x97241440.

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Visual feedback regulation during movement is not fully captured in Plamondon's kinematic theory. However, numerous studies indicate that visual response-produced feedback is a powerful determinant of performance and kinematic characteristics of target-directed movement.

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35

Shao, Sichen, and Ramanujan S. Hegde. "Target Selection during Protein Quality Control." Trends in Biochemical Sciences 41, no. 2 (2016): 124–37. http://dx.doi.org/10.1016/j.tibs.2015.10.007.

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36

Nishi, Rae. "Target-mediated control of neural differentiation." Progress in Neurobiology 69, no. 4 (2003): 213–27. http://dx.doi.org/10.1016/s0301-0082(03)00046-7.

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37

SCHNEIDER, MARY ELLEN. "Joint Commission Rules Target Infection Control." Family Practice News 38, no. 15 (2008): 8. http://dx.doi.org/10.1016/s0300-7073(08)70945-9.

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38

Yan, Kelley S., and Ming-Ming Zhou. "TAGging the target for damage control." Nature Structural Biology 9, no. 9 (2002): 638–40. http://dx.doi.org/10.1038/nsb0902-638.

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39

Drenick, R. F. "Target-Directed Control of Nonlinear Systems." IFAC Proceedings Volumes 22, no. 3 (1989): 89–94. http://dx.doi.org/10.1016/s1474-6670(17)53615-0.

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40

Tani, Takeyuki. "Interactive control in target cost management." Management Accounting Research 6, no. 4 (1995): 399–414. http://dx.doi.org/10.1006/mare.1995.1028.

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41

O’Connor, Shawn, and Anne Philipneri. "Monitoring Tobacco Control Outcomes: The Unintended Consequences of Target Selection." Canadian Journal of Program Evaluation 24, no. 3 (2010): 25–38. http://dx.doi.org/10.3138/cjpe.0024.002.

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Abstract: We explore key lessons arising out of target-setting agendas in tobacco control. Two real-world examples are described that illustrate the pitfalls of choosing an omnibus target for a comprehensive strategy: (a) a target to reduce wholesale cigarette sales in Ontario and (b) a First Ministers’ target to reduce current smoking. Changing contexts brought about by shifts in illicit tobacco sales made it problematic to interpret success in both cases. The discussion draws attention to key considerations in setting targets, including unintended consequences, data quality, ideal number, an

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42

Tommaselli, Antonio Maria Garcia, and Adilson Berveglieri. "MEASURING PHOTOGRAMMETRIC CONTROL TARGETS IN LOW CONTRAST IMAGES." Boletim de Ciências Geodésicas 24, no. 2 (2018): 171–85. http://dx.doi.org/10.1590/s1982-21702018000200012.

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Abstract: This paper presents an experimental assessment of photogrammetric targets and subpixel location techniques to be used with low contrast images such as images acquired by hyperspectral frame cameras. Eight different target patterns of varying shape, background, and size were tested. The aim was to identify an optimum distinctive pattern to serve as control point in aerial surveys of small areas using hyperspectral cameras when natural points are difficult to find in suitable areas. Three automatic techniques to identify the target point of interest were compared, which were weighted c

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43

Ort, Eduard, Johannes Fahrenfort, and Christian Olivers. "Control over target selection determines switch costs in multiple-target search." Journal of Vision 16, no. 12 (2016): 1287. http://dx.doi.org/10.1167/16.12.1287.

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44

Jiang, Guangsheng, Xianming Shi, Mei Zhao, Yuan Li, and Kang Li. "Research on Weapon Target Allocation of Synthetic Detachment Considering Emergency Target." E3S Web of Conferences 235 (2021): 03041. http://dx.doi.org/10.1051/e3sconf/202123503041.

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In view of the problem of emergency target handling and reasonable attack in the combat process of synthetic detachment, this paper analyzes the main characteristics of emergency target, judges the threat degree of emergency target with “threat factor function”, and controls the output of the solution by solving the objective function of “threat factor function”, so as to ensure that the emergency target with great influence can be handled quickly. By improving the weapon target allocation model and using the solution control strategy, the simulation results show that this method can effective

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45

De Lima Dias, Sanailton, Francisco Tavares Filho, André Luis Korzenowski, Moisés Ozório de Souza Neto, and Rafael Ramon Fonsêca Rodrigues. "Target costing." International Journal for Innovation Education and Research 9, no. 11 (2021): 491–510. http://dx.doi.org/10.31686/ijier.vol9.iss11.3542.

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The implementation of a cost control system in construction companies contributes to reducing resource losses in the production process and increasing business productivity and profitability, especially when it comes to small business, which normally do not have a planning system and efficient control. Therefore, this article aims to propose a target costing model for a small construction business, concerning the efficient evaluation of its costs for the maximization of profits in proposals to provide services to public entities. A case study is used, in which data collection occurred through

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46

Pang, Yan, Michael P. Spathopoulos, and Hao Xia. "Suboptimal target control for hybrid automata using model predictive control." Nonlinear Analysis: Theory, Methods & Applications 65, no. 6 (2006): 1211–30. http://dx.doi.org/10.1016/j.na.2005.12.025.

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47

Asfihani, Tahiyatul, Mirzaq Khoirul Mufidah, Subchan Subchan, and Dieky Adzkiya. "Missile Control Design for Moving Target using Model Predictive Control." Journal of Physics: Conference Series 1490 (March 2020): 012069. http://dx.doi.org/10.1088/1742-6596/1490/1/012069.

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48

Chen, Yougen, and Seiji Yasunobu. "Soft-Target-Based Predictive Fuzzy Control for a Cart-Pendulum System with Dynamic Constraints." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 8 (2007): 931–36. http://dx.doi.org/10.20965/jaciii.2007.p0931.

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Human decisions to act are based on broad targets and respond flexibly in different situations. Such, self-adaptation to dynamic constraints is difficult but important for autonomous control. Conventional control usually uses a single target that results in inflexibility in responding to dynamic environments such as changes in constraints. We propose a predictive fuzzy intelligent controller based on soft targets defined as a series of target sets that include many target elements with different satisfaction grades and are converted to target setting knowledge by fuzzy logic. This controller w

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49

Pernezny, K., P. Stoffella, J. Collins, A. Carroll, and A. Beaney. "Control of target spot of tomato with fungicides, systemic acquired resistance activators, and a biocontrol agent." Plant Protection Science 38, No. 3 (2012): 81–88. http://dx.doi.org/10.17221/4855-pps.

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Control of target spot of tomato, caused by the fungus Corynespora cassiicola (Berk. &amp; Curt.) Wei., was studied in three seasons in southern Florida, USA. The strobilurin fungicide azoxystrobin and a combination product of mancozeb and fumoxate provided excellent control of target spot. In these treatments, accumulated disease severity values were only 10&ndash;15% of those in the untreated control and marketable yields were doubled. Excellent disease control also was achieved with acibenzolar-S-methyl, a systemic acquired resistance activator (SAR). This compound reduced defoliati

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50

Hayes, Sean T., and Julie A. Adams. "Adaptive Control-Display Ratios for Smartphones." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (2016): 815–19. http://dx.doi.org/10.1177/1541931213601186.

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Smartphones pose new design challenges for precise interactions, prompting the development of indirect interaction techniques that improve performance by reducing the occlusion caused by touch input. Direct touch interaction (e.g., tap to select) is imprecise, due to occlusion and the finger’s surface area. Many cursor-based interaction techniques address this issue; however, these techniques do not dynamically adjust the control-to-display movement ratio ( CDratio ) to improve accuracy and interaction times. This paper analyzes the performance benefits of applying adaptive CDratio enhancement

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