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Journal articles on the topic 'Filtering effects'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Dakin, Steven C. "Glass Patterns: Some Contrast Effects Re-Evaluated." Perception 26, no. 3 (1997): 253–68. http://dx.doi.org/10.1068/p260253.

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The relative contrast of features is known to be important in determining if they can be grouped. Two manipulations of feature contrast have previously been used to criticise models of visual grouping based on spatial filtering: high-pass filtering and reversal of contrast polarity. The effects of these manipulations are considered in the context of the perception of Glass patterns. It is shown that high-pass filtering elements, whilst destroying structure in the output of low-pass filters, do not significantly disrupt the output of locally band-pass filters. The finding that subjects can perc

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2

Cioffi, J. "Limited-precision effects in adaptive filtering." IEEE Transactions on Circuits and Systems 34, no. 7 (1987): 821–33. http://dx.doi.org/10.1109/tcs.1987.1086209.

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Borcea, L., F. González del Cueto, G. Papanicolaou, and C. Tsogka. "Filtering Random Layering Effects in Imaging." Multiscale Modeling & Simulation 8, no. 3 (2010): 751–81. http://dx.doi.org/10.1137/090760854.

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4

Borcea, L., F. González del Cueto, G. Papanicolaou, and C. Tsogka. "Filtering Deterministic Layer Effects in Imaging." SIAM Review 54, no. 4 (2012): 757–98. http://dx.doi.org/10.1137/120880975.

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5

Ye, Zhirui, Yuan Wang, and Yuan Wen. "Effects of Information Filtering on Driving." Procedia - Social and Behavioral Sciences 96 (November 2013): 1755–63. http://dx.doi.org/10.1016/j.sbspro.2013.08.200.

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6

Deffuant, Guillaume, and Sylvie Huet. "Propagation effects of filtering incongruent information." Journal of Business Research 60, no. 8 (2007): 816–25. http://dx.doi.org/10.1016/j.jbusres.2007.02.001.

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Jiménez-Ceniceros, Antonio, and Victor M. Castaño Meneses. "Interference Effects Using Ring-Shaped Filtering." Optical Review 10, no. 6 (2003): 518–22. http://dx.doi.org/10.1007/s10043-003-0518-5.

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8

Carroll, T. L., and Frederic J. Rachford. "Using filtering effects to identify objects." Chaos: An Interdisciplinary Journal of Nonlinear Science 22, no. 2 (2012): 023107. http://dx.doi.org/10.1063/1.3702566.

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9

Borcea, L., F. González del Cueto, G. Papanicolaou, and C. Tsogka. "Filtering Deterministic Layer Effects in Imaging." Multiscale Modeling & Simulation 7, no. 3 (2009): 1267–301. http://dx.doi.org/10.1137/080731529.

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10

Webb, G. R., S. Redman, C. Wilkinson, and R. W. Sanson-Fisher. "Filtering effects in reporting work injuries∗." Accident Analysis & Prevention 21, no. 2 (1989): 115–23. http://dx.doi.org/10.1016/0001-4575(89)90081-x.

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11

Saindon, Rosanna, and T. M. Whitworth. "Membrane effects during filtering investigation of membrane effects during filtering of natural surface waters in Missouri." Aquatic Geochemistry 12, no. 4 (2006): 365–74. http://dx.doi.org/10.1007/s10498-006-9002-8.

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12

Srinivasa, K. G., N. Pramod, K. R. Venugopal, and L. M. Patnaik. "Effects of Information Filters." International Journal of Information Retrieval Research 2, no. 2 (2012): 1–12. http://dx.doi.org/10.4018/ijirr.2012040101.

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In the Internet era, information processing for personalization and relevance has been one of the key topics of research and development. It ranges from design of applications like search engines, web crawlers, learning engines to reverse image searches, audio processed search, auto complete, etc. Information retrieval plays a vital role in most of the above mentioned applications. A part of information retrieval which deals with personalization and rendering is often referred to as Information Filtering. The emphasis of this paper is to empirically analyze the information filters commonly see

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13

Jamali, Hamid R., and Pria Shahbaztabar. "The effects of internet filtering on users’ information-seeking behaviour and emotions." Aslib Journal of Information Management 69, no. 4 (2017): 408–25. http://dx.doi.org/10.1108/ajim-12-2016-0218.

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Purpose The purpose of this paper is to investigate the relationship between internet filtering, emotions and information-seeking behaviour. Design/methodology/approach In total, 15 postgraduate students at an Iranian university participated in the study which involved a questionnaire, search tasks with think aloud narratives, and interviews. Findings Internet content filtering results in some changes in the information-seeking behaviour of users. Users who face website blocking use a variety of methods to bypass filtering, mostly by using anti-filter software. Filtering encourages users to us

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14

Ab Latip, Amir Sharifuddin, Andi Mohd Hairy Ansar, Ami Hassan Md Din, and Abdul Lateef Balogun. "Correcting Atmospheric Effects on the InSAR Measurements using GPS Data." IOP Conference Series: Earth and Environmental Science 1067, no. 1 (2022): 012043. http://dx.doi.org/10.1088/1755-1315/1067/1/012043.

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Abstract The effect of the atmospheric error in the spaceborne synthetic aperture radar (SAR) signal is more prominent in Malaysia due to its hot and wet conditions. Because the atmospheric error is believed to happen constantly in space and randomly in time, low-pass filtering in space and high-pass filtering in time is employed to measure it. However, with few scenes, the filtering technique’s reliability in removing atmospheric error may be insufficient, leading to erroneous surface deformation. Therefore, an external atmospheric correction needs to be modelled to improve the accuracy of su

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Gamboa, Luis E., Jean-Philippe Guertin, and Derek Nowrouzezahrai. "Scalable appearance filtering for complex lighting effects." ACM Transactions on Graphics 37, no. 6 (2019): 1–13. http://dx.doi.org/10.1145/3272127.3275058.

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16

Rosenstein, Michael T., and James J. Collins. "Visualizing the effects of filtering chaotic signals." Computers & Graphics 18, no. 4 (1994): 587–92. http://dx.doi.org/10.1016/0097-8493(94)90072-8.

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17

Jordan, I. K., C. J. Rossouw, and R. Vincent. "Effects of energy filtering in LACBED patterns." Ultramicroscopy 35, no. 3-4 (1991): 237–43. http://dx.doi.org/10.1016/0304-3991(91)90075-h.

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18

Blaimer, Martin, Irene P. Ponce, Felix A. Breuer, Peter M. Jakob, Mark A. Griswold, and Peter Kellman. "Temporal filtering effects in dynamic parallel MRI." Magnetic Resonance in Medicine 66, no. 1 (2011): 192–98. http://dx.doi.org/10.1002/mrm.22795.

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19

Morozov, Igor, Mohamed Haiba, and Wubing Deng. "Inverse attenuation filtering." GEOPHYSICS 83, no. 2 (2018): V135—V147. http://dx.doi.org/10.1190/geo2016-0211.1.

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Inverse-[Formula: see text] filtering is an important seismic-processing operation often used to correct for attenuation and dispersion effects and increase the resolution of reflection records. However, it is important to realize that the [Formula: see text] is an apparent (phenomenological) attribute of the propagating wavefield and not guaranteed to be a material property. By recognizing the apparent character of the [Formula: see text], the attenuation-correction procedure can be significantly extended and generalized. Our approach consists of forward modeling the propagating source wavefo

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20

Bannawat, Lakkhana, Akkarat Boonpoonga, Santana Burintramart, and Prayoot Akkaraekthalin. "On the Resolution Improvement of Radar Target Identification with Filtering Antenna Effects." International Journal of Antennas and Propagation 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/3405908.

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An investigation on the improvement of the resolution of a radar target identification system is presented in this paper. Degradation of resolution is mainly due to influence factors associated with antennas, including the strong coupling between transmitting and receiving antennas and the variation in the antenna response. A filtering technique was therefore introduced to mitigate the underlying problem. In the technique, the antenna effects were filtered out of the total response backscattered from the objects in the radar target identification system. The short-time matrix pencil method (ST

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21

Zheng, Yi, Jun Yue, Xiao Feng Sun, and Jian Chen. "Studies of Filtering Effect on Internal Solitary Wave Flow Field Data in the South China Sea Using EMD." Advanced Materials Research 518-523 (May 2012): 1422–25. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.1422.

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Based on the scheme of Empirical Mode Decomposition(EMD), different low pass filtering algorithms were derived from Intrinsic Mode Function (IMF), then the rules to select superior filtering algorithms were established by minimum noise energy principles and filtering flatness indicators. The superior filtering algorithms proved to be theoretically effective and reasonable. The study finally revealed the filtering algorithm without the first four IMFs was the best. Utilizing the internal waves flow field data observed in the South China Sea, the filtering effect on the waves’ velocity propagati

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22

Telegina, M. V. "Selective effects of centroid filtering for noisy images." Optoelectronics, Instrumentation and Data Processing 43, no. 5 (2007): 419–24. http://dx.doi.org/10.3103/s8756699007050044.

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23

NITTONO, Hiroshi, and Keiichi ONODA. "Effects of filtering on event-related potential waveforms." Japanese Journal of Physiological Psychology and Psychophysiology 26, no. 3 (2008): 237–46. http://dx.doi.org/10.5674/jjppp1983.26.237.

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24

Liao, Xiaofeng, Hu Wu, and Yongji Wang. "Ant Collaborative Filtering Addressing Sparsity and Temporal Effects." IEEE Access 8 (2020): 32783–91. http://dx.doi.org/10.1109/access.2020.2973931.

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25

Walborn, S. P., P. H. Souto Ribeiro, and C. H. Monken. "Interference effects induced by non-local spatial filtering." Optics Express 19, no. 18 (2011): 17308. http://dx.doi.org/10.1364/oe.19.017308.

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26

Liu, Jin-Hu, Zi-Ke Zhang, Lingjiao Chen, Chuang Liu, Chengcheng Yang, and Xueqi Wang. "Gravity Effects on Information Filtering and Network Evolving." PLoS ONE 9, no. 3 (2014): e91070. http://dx.doi.org/10.1371/journal.pone.0091070.

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27

Nicholson, Nannette. "EFFECTS OF FILTERING AND RE-WINDOWING ON TEOAE." Hearing Journal 57, no. 9 (2004): 12. http://dx.doi.org/10.1097/01.hj.0000292836.44494.29.

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28

Gu, Qiongchan, Bowen Xu, Hang Zhao, Sheng Hu, Xiaoxiao Jiang, and Jiangtao Lv. "Plasmonic Photothermal Effects Based on Dynamic Optical Filtering." Nanoscience and Nanotechnology Letters 9, no. 11 (2017): 1605–21. http://dx.doi.org/10.1166/nnl.2017.2535.

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29

Liu, Chang, and David A. Eddins. "Effects of spectral modulation filtering on vowel identification." Journal of the Acoustical Society of America 124, no. 3 (2008): 1704–15. http://dx.doi.org/10.1121/1.2956468.

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30

Nagai, Minoru, Kazuaki Inaba, Kosuke Takahashi, and Kikuo Kishimoto. "Filtering Effects of Periodic Structure in Water Hammer." Applied Mechanics and Materials 566 (June 2014): 50–55. http://dx.doi.org/10.4028/www.scientific.net/amm.566.50.

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In this study, we conducted water hammer experiments in the tube which was periodically supported by various numbers of clamps, named periodic structure, initiated by a projectile impact. The parts of the polycarbonate (PC) tube supported by 1-7 steel clamps make the tube stiffer and heavier than the original PC tube and are expected to cause a filtering effect of the frontal frequency components in the water hammer. According to our experimental observations, we confirmed that higher frequency components more than 1 kHz in the wave front were attenuated and the peak strains in circumferential

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Otte, V. A., P. R. Almond, J. B. Smathers, and F. H. Attix. "Skin-sparing effects of neutron beam filtering materials." Medical Physics 14, no. 4 (1987): 670–73. http://dx.doi.org/10.1118/1.596146.

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32

Yaldo, Mazin K. "Long-term Effects of Mitomycin on Filtering Blebs." Archives of Ophthalmology 111, no. 6 (1993): 824. http://dx.doi.org/10.1001/archopht.1993.01090060112033.

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33

Brownell, Alexander A., and Mark B. Bromberg. "Effects of high-pass filtering on MUAP metrics." Muscle & Nerve 40, no. 6 (2009): 1008–11. http://dx.doi.org/10.1002/mus.21429.

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34

Li, Jian, and Xiuhai Zhao. "Modification of Density Dependence and Habitat Filtering on Seedling Survival of Different Mycorrhizal-Type Tree Species in Temperate Forests." Forests 14, no. 9 (2023): 1919. http://dx.doi.org/10.3390/f14091919.

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Conspecific negative density dependence (CNDD) and habitat filtering are critical to seedling survival. However, the relative importance of the two processes in affecting survival of seedlings with different types of mycorrhizae remains unclear. In this study, the effects of CNDD and habitat filtering on the survival of tree seedlings with different mycorrhizal types were investigated at different successional stages of a temperate forest in the Changbai Mountain Natural Reserve, Northeast China. Conspecific negative density dependence and habitat filtering significantly affected seedling surv

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35

Li, Changling, Xiaoxia Luo, Xianghu Huang, and Binhe Gu. "Effects of Temperature, Salinity, pH, and Light on Filtering and Grazing Rates of a Calanoid Copepod (Schmackeria dubia)." Scientific World JOURNAL 8 (2008): 1219–27. http://dx.doi.org/10.1100/tsw.2008.153.

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Calanoid copepods are key components of the marine food web and the food sources of many larval fishes and planktivores, and grazers of phytoplankton. Understanding the ranges of major environmental variables suitable for their growth is essential to maintain the balance between trophic links and resources protection. In this study, the effects of temperature, salinity, pH, and light intensity on the filtering and grazing rates of a herbivorous copepod (Schmackeria dubia) were conducted in several control experiments. Our results indicated that experimental animals grazed normally at water tem

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Rahman, Shadab A., Shai Marcu, Colin M. Shapiro, Theodore J. Brown, and Robert F. Casper. "Spectral modulation attenuates molecular, endocrine, and neurobehavioral disruption induced by nocturnal light exposure." American Journal of Physiology-Endocrinology and Metabolism 300, no. 3 (2011): E518—E527. http://dx.doi.org/10.1152/ajpendo.00597.2010.

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The human eye serves distinctly dual roles in image forming (IF) and non-image-forming (NIF) responses when exposed to light. Whereas IF responses mediate vision, the NIF responses affect various molecular, neuroendocrine, and neurobehavioral variables. NIF responses can have acute and circadian phase-shifting effects on physiological variables. Both the acute and phase-shifting effects induced by photic stimuli demonstrate short-wavelength sensitivity peaking ≈450–480 nm. In the current study, we examined the molecular, neuroendocrine, and neurobehavioral effects of completely filtering (0% t

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Mann, D., E. Staykov, S. Sands, and P. Terrill. "O040 Investigating the effects of airflow signal filtering on non-invasively quantified estimates of flow limitation." Sleep Advances 5, Supplement_1 (2024): A15. https://doi.org/10.1093/sleepadvances/zpae070.040.

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Abstract Introduction We previously reported a method to estimate flow limitation (FL, range 0-~1) from the airflow signal recorded within a polysomnogram. This method utilised high quality nasal pressure signals, without high-pass (HP) filtering. However, many clinical recording systems implement HP filtering on airflow signals. We hypothesised that FL estimates would be adversely affected when airflow signals have HP filtering present. Methods Within our existing framework for estimating FL, we manipulated the airflow signal by applying digital HP filtering (Butterworth, 4th order) at common

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38

Rahman, Md Bayzidur, Tim Driscoll, Mark Clements, Bruce K. Armstrong, and Christine T. Cowie. "Effects of tap water processing on the concentration of disinfection by-products." Journal of Water and Health 9, no. 3 (2011): 507–14. http://dx.doi.org/10.2166/wh.2011.155.

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Aim: This study examined the effects on disinfection by-product (DBP) concentrations of common household methods for processing drinking water. Methods: We investigated the effects of refrigerator storage, jug filtering, boiling in an electric kettle, and supply from an instant boiling water unit, with or without filtering, on four species of trihalomethanes (THMs) and nine species of haloacetic acids (HAAs) in water ready for consumption in Sydney, Australia. Water samples were processed in such a way as to simulate real life conditions for drinking filtered water or hot water drinks prepared

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39

Brown, J. A., and C. Green. "Single nephron function of the lesser spotted dogfish, Scyliorhinus canicula, and the effects of adrenaline." Journal of Experimental Biology 129, no. 1 (1987): 265–78. http://dx.doi.org/10.1242/jeb.129.1.265.

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Function of the kidney and the nephron in the lesser spotted dogfish, Scyliorhinus canicula, was investigated by clearance, renal tubular micropuncture and ferrocyanide infusion techniques. 70% of the glomerular filtrate was reabsorbed within the renal tubule, producing slightly hypotonic urine. Glomeruli were: perfused and filtering (F); arterially perfused but not filtering (NF); or non-arterially perfused and hence not filtering (NP). Adrenaline reduced the proportion of filtering glomeruli from 94% to 70%. Despite this reduction, a marked overall glomerular diuresis occurred. Single nephro

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40

Mattos Júnior, Adolfo Paulo de, та Maria José dos Santos Wisniewski. "Xenohormones cloprostenol, estrone and 17α-etinilestradiol alters filtering rates of the tropical cladoceran Ceriodaphnia silvestrii Daday 1902". Regnellea Scientia 7, № 1 (2021): 29–40. http://dx.doi.org/10.61202/2525-4936.v7.n1.2021.29-40.

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Emergent contaminants found in water bodies are being studied for its effects on the biota and the ecosystem. Endocrine disrupting compounds are a subset that can affect survivability, reproduction and filtering of zooplankton specimens when exposed to these xenocompounds. This study assessed filtering rates of Ceriodaphnia silvestrii specimens exposed to increasing concentration of cloprostenol, 17α-ethynilestradiol and estrone, and found that cloprostenol decreased filtering rates at all concentrations assessed (p= 0.0254), estrone increased filtering in a concentration-wise manner (p= 0.007

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41

Wang, Li Di, Jiang Feng Tang, and Jun Sheng Shi. "Parameter Identification for the Dynamic Load Modeling Based on Denoising Method of the Measurement Data." Advanced Materials Research 217-218 (March 2011): 907–10. http://dx.doi.org/10.4028/www.scientific.net/amr.217-218.907.

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Different denoising methods are used in parameter identification for the dynamic load modeling and the specific approach is proposed. The effects of different denoising methods including mean filtering, medial filtering and wavelet denoising are discussed. Mean filtering method is not helpful to contain the step changes of the measurement voltage, thus is unsuitable for the parameter identification process. Medial filtering method and wavelet denoising methods are suitable for the parameter identification in dynamic load modeling. Furthermore, experiment results based on the measurement data s

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42

Hyung, Sung Min, Dong Myung Kim, Chul Hong, and Dong Ho Youn. "Effects of aqueous humor on filtering bleb in rabbits." Korean Journal of Ophthalmology 6, no. 1 (1992): 6. http://dx.doi.org/10.3341/kjo.1992.6.1.6.

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Park, Myung-Su, and Ji-Sang Yoo. "Filtering for reducing aliasing effects on auto-multiscopic monitor." Journal of Broadcast Engineering 15, no. 4 (2010): 591–99. http://dx.doi.org/10.5909/jbe.2010.15.4.591.

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LIU, LEI, JIAN-GUO LIU, JING NI, et al. "EFFECTS OF THE HIGH-ORDER CORRELATION ON INFORMATION FILTERING." International Journal of Modern Physics C 23, no. 06 (2012): 1250045. http://dx.doi.org/10.1142/s0129183112500453.

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In this paper, we empirically investigate the statistical properties of the user correlation network in terms of their common rated objects on MovieLens, and find that it has high clustering coefficient and ultra small average distance, which is close to the fully connected network. We argue that the above characteristics come from the fact that large-degree objects build lots of fully connected subnetworks by using the node projection method. By introducing the user global similarity, measured by the product of two users' similarity vectors, we present an effective way to identify users' spec

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45

Moore, Robert E., Elizabeth M. Adams, Paul A. Dagenais, and Carrie Caffee. "Effects of reverberation and filtering on speech rate judgment." International Journal of Audiology 46, no. 3 (2007): 154–60. http://dx.doi.org/10.1080/14992020601126831.

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Lemone, Margaret A., Tae Y. Chang, and Christopher Lucas. "On the Effects of Filtering on Convective-Core Statistics." Journal of the Atmospheric Sciences 51, no. 22 (1994): 3344–50. http://dx.doi.org/10.1175/1520-0469(1994)051<3344:oteofo>2.0.co;2.

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Hrbek, Sara J., Nagaraj C. Shivaramaiah, and Dennis M. Akos. "Filtering and Quantization Effects on GNSS Successive Interference Cancellation." IEEE Transactions on Aerospace and Electronic Systems 56, no. 2 (2020): 924–36. http://dx.doi.org/10.1109/taes.2019.2935959.

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Mehta, Soham Uday, JiaXian Yao, Ravi Ramamoorthi, and Fredo Durand. "Factored axis-aligned filtering for rendering multiple distribution effects." ACM Transactions on Graphics 33, no. 4 (2014): 1–12. http://dx.doi.org/10.1145/2601097.2601113.

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van Duren, Luca A., Peter M. J. Herman, Adri J. J. Sandee, and Carlo H. R. Heip. "Effects of mussel filtering activity on boundary layer structure." Journal of Sea Research 55, no. 1 (2006): 3–14. http://dx.doi.org/10.1016/j.seares.2005.08.001.

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50

Mantsevich, V. N., N. S. Maslova, and P. I. Arseyev. "Non-stationary spin-filtering effects in correlated quantum dot." Physica E: Low-dimensional Systems and Nanostructures 93 (September 2017): 224–29. http://dx.doi.org/10.1016/j.physe.2017.06.027.

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