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Статті в журналах з теми "Processing"

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Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 29 липня 2024

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1

Takahashi, Hiroki. "Processing." Journal of The Institute of Image Information and Television Engineers 64, no. 12 (2010): 1841–49. http://dx.doi.org/10.3169/itej.64.1841.

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2

Mallidi, Sudhakara Reddy, and Gottipalla Ashok Kumar. "A Comparison of Query Processing Architectures and Transaction Processing." International Journal of Scientific Research 2, no. 4 (June 1, 2012): 152–53. http://dx.doi.org/10.15373/22778179/apr2013/53.

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3

Mehraj, Nadiya, and Harveen Kour. "Data Processing Through Image Processing using Gaussian Minimum Shift Keying." International Journal of Trend in Scientific Research and Development Volume-2, Issue-6 (October 31, 2018): 977–81. http://dx.doi.org/10.31142/ijtsrd18819.

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4

Patel, Stuti. "Natural Language Processing." International Journal of Science and Research (IJSR) 12, no. 2 (February 5, 2023): 1123–29. http://dx.doi.org/10.21275/sr23216193027.

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5

Lee, Tatia M. C. "Plenary B: The Pons is a Significant Neural Correlate of Affective Processing." Journal of the International Neuropsychological Society 29, s1 (November 2023): 501. http://dx.doi.org/10.1017/s1355617723006483.

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Анотація:

Abstract & Learning Objectives:Research on the role of the Pons in affective processing has been scarce. Recent animal work has shown that the direct projection from the eyes to the dorsal raphe nucleus modulates affective behaviours. Our previous human work has confirmed a functionally analogous pathway between the optic chiasm and the Pons, which facilitates the processing of negative affective information. Our other studies have further identified that the Pons (1) works with the distributed corticolimbic system to shape an individual's affective states and reactivity and (2) responds to short-term meditation training to modulate affective processing. These findings offer significant insight into the role of the Pons in affective processing and regulatory mechanisms.Upon conclusion of this course, learners will be able to: 1.Discuss the functional roles of the pons in affective processing2.Recognize that the pons is a significant neural correlate of affective processing3.List major neural correlates of the affective processing network

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6

Perkowski, Lisa M. "Processing Film, Processing Meaning." Art Education 68, no. 3 (May 2015): 32–38. http://dx.doi.org/10.1080/00043125.2015.11519320.

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7

Van Dantzig, Saskia, Diane Pecher, René Zeelenberg, and Lawrence W. Barsalou. "Perceptual Processing Affects Conceptual Processing." Cognitive Science 32, no. 3 (April 5, 2008): 579–90. http://dx.doi.org/10.1080/03640210802035365.

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8

Navon, David, and Dov Pearl. "Preattentive processing or prefocal processing?" Acta Psychologica 60, no. 2-3 (December 1985): 245–62. http://dx.doi.org/10.1016/0001-6918(85)90057-5.

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9

Itybayeva, G. T., G. M. Bazhenov, A. Zh Kasenov, A. S. Yanushkin, and K. K. Abishev. "Processing of flat glass." BULLETIN of L.N. Gumilyov Eurasian National University. Technical Science and Technology Series 138, no. 1 (2022): 34–43. http://dx.doi.org/10.32523/2616-7263-2022-138-1-34-43.

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Анотація:

The article discusses the issues of sheet glass processing and provides information about the application, advantages, disadvantages and technological capabilities. The technological parameters of waterjet processing that affect to the cutting quality: the jet speed, the grain size of the abrasive, the angle of jet inclination, the distance from the nozzle to the treated surface. The water cutting method or waterjet cutting can significantly increase the speed and quality of material cutting. From an economic point of view, the consumption of material and energy is significantly reduced (by 20-30%), due to the use of water energy as the cutting tool in this method. The consumable material is only water and abrasive material. By modeling, when using software, it is proved that during waterjet cutting, lower stresses are formed in the glass compared to mechanical roller cutting, thereby ensuring minimal heat generation and accurate cutting with an edge roughness of Ra 1.6 microns.

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10

Mirzaakbarovna, Mirzababayeva Sahiba, and Tursunov Narimonjon Sultanbayevich. "Wood Processing For Construction." American Journal of Applied sciences 03, no. 05 (May 31, 2021): 186–89. http://dx.doi.org/10.37547/tajas/volume03issue05-29.

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11

Hanai, Saki, and Mitsuhiro Suzuki. "SOUND PROCESSING APPARATUS, SOUND PROCESSING METHOD, AND SOUND PROCESSING PROGRAM." Journal of the Acoustical Society of America 134, no. 5 (2013): 3962. http://dx.doi.org/10.1121/1.4828904.

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12

Ford, Chris. "Processing." Technology|Architecture + Design 3, no. 1 (January 2, 2019): 2–3. http://dx.doi.org/10.1080/24751448.2019.1571789.

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13

SHOJI, SHIGETOSHI. "Processing." NIPPON GOMU KYOKAISHI 69, no. 8 (1996): 539–41. http://dx.doi.org/10.2324/gomu.69.539.

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14

Elbein, Alan D. "Glycoprotein Processing and Glycoprotein Processing Inhibitors." Plant Physiology 87, no. 2 (June 1, 1988): 291–95. http://dx.doi.org/10.1104/pp.87.2.291.

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15

Franceschetti, Giorgio, Antonio Lodice, and Manlio Tesauro. "From image processing to feature processing." Signal Processing 60, no. 1 (July 1997): 51–63. http://dx.doi.org/10.1016/s0165-1684(97)00064-9.

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16

TAKAHASHI, Tadashi. "Material processing by lasers. Thermal processing." Review of Laser Engineering 15, no. 6 (1987): 413–19. http://dx.doi.org/10.2184/lsj.15.413.

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17

Manolakos, E. S., H. M. Stellakis, and D. H. Brooks. "Parallel processing for biomedical signal processing." Computer 24, no. 3 (March 1991): 33–43. http://dx.doi.org/10.1109/2.73511.

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18

Sōmiya, Ahigeyuki, K. Hishinuma, and Tokuji Akiba. "A new materials processing—hydrothermal processing." Bulletin of Materials Science 18, no. 6 (October 1995): 811–18. http://dx.doi.org/10.1007/bf02744811.

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19

Bardhan, Yash, Tejas A. Fulzele, and Prabhat Ranjan Shekhar Upadhyay Prof V. D. Bharate. "Emotion Recognition using Image Processing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1523–26. http://dx.doi.org/10.31142/ijtsrd10995.

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20

Dr G.Nagamani, Dr G. Nagamani. "Processing Technology For Tomato Powder." International Journal of Scientific Research 3, no. 2 (June 1, 2012): 210–13. http://dx.doi.org/10.15373/22778179/feb2014/69.

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21

G., Shete S., and Ghadge Nagnath G. "Image Processing in MATLAB 9.3." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (February 28, 2018): 925–29. http://dx.doi.org/10.31142/ijtsrd9545.

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22

Gaikwad, Anil P., and Bhagyashri R. More. "Digital Watermarking for Image Processing." Paripex - Indian Journal Of Research 2, no. 1 (January 15, 2012): 65–67. http://dx.doi.org/10.15373/22501991/jan2013/24.

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23

Batirov, Behzod. "MEDICAL PROCESSING OF CARIOUS CAVITY." UZBEK MEDICAL JOURNAL 2, no. 1 (February 28, 2020): 60–63. http://dx.doi.org/10.26739/2181-0664-2020-2-9.

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24

Klyuchko, O. M. "TECHNOLOGIES OF BRAIN IMAGES PROCESSING." Biotechnologia Acta 10, no. 6 (December 2017): 5–17. http://dx.doi.org/10.15407/biotech10.06.005.

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25

Bogdanov, Andrey. "NEW APPLICATOIN OF LOGISTICS PROCESSING." Journal Scientific and Applied Research 20, no. 1 (November 12, 2020): 47–52. http://dx.doi.org/10.46687/jsar.v20i1.304.

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26

KOMATSUBARA, Nobuaki, and Etsuji OHMURA. "A012 Internal Processing of Glass by Ultrashort Pulse Laser and Analysis of Its Processing Phenomena." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2013.7 (2013): 55–58. http://dx.doi.org/10.1299/jsmelem.2013.7.55.

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27

Peyre, Gabriel. "The Numerical Tours of Signal Processing Part 2: Multiscale Processings." Computing in Science & Engineering 13, no. 5 (September 2011): 68–71. http://dx.doi.org/10.1109/mcse.2011.90.

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28

Kroneisen, Meike, Jan Rummel, and Edgar Erdfelder. "What kind of processing is survival processing?" Memory & Cognition 44, no. 8 (August 1, 2016): 1228–43. http://dx.doi.org/10.3758/s13421-016-0634-7.

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29

Kang, Di, Youhua Fan, Zejun Chen, Fang Ma, Shaofeng Peng, and Yong Wang. "Fruit Processing Equipment based on Model Processing." Journal of Physics: Conference Series 2066, no. 1 (November 1, 2021): 012111. http://dx.doi.org/10.1088/1742-6596/2066/1/012111.

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Анотація:

Abstract The technology and equipment of this study can improve the technical level of the equipment for peeling and cleaning of Camellia oleifera fruit. Based on the biological characteristics of Camellia oleifera fruit, the size distribution model of Camellia oleifera fruit was established, and the equipment structure and key parameters were determined based on the working principle and design method of the shelling and cleaning mechanism. Based on the analysis of the movement track of the shell stripping and cleaning executive parts, the test scheme is established, and it is optimized that when the crankshaft speed is 240-260r/min and the track speed is 0.4-0.6m/s, the treatment capacity can reach the level of 2000kg/h, and the purification rate is more than 99%. When the vibration frequency of the vibrating motor is set to 50Hz and the horizontal inclination of the separation belt is 50 ° ∼ 55 °, the cleaning effect of the equipment is the best.

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30

Sharma, Sushma, Hitesh Kumar, and Charul Thareja. "Digital Signal Processing Over Analog Signal Processing." Journal of Advance Research in Electrical & Electronics Engineering (ISSN: 2208-2395) 1, no. 2 (February 28, 2014): 01–02. http://dx.doi.org/10.53555/nneee.v1i2.255.

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Анотація:

This paper provides a survey of digital signal processing over analog signal processing. Initially digital signal processing is developed to replace limited application based analog signal processing (ASP) of high cost. This paper describes the comparison of analog signal processing (ASP) and digital signal processing, technology under digital signal processing , application of digital signal processing, new technology of digital signal processing (DSP). This paper also focuses on the future scope of digital signal processing (DSP).

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31

HIFUMI, TOMOKO. "Relationship of Linguistic Processing and Psychological Processing." Japanese Journal of Educational Psychology 47, no. 4 (1999): 490–500. http://dx.doi.org/10.5926/jjep1953.47.4_490.

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32

Chen, F. C. F., and M. H. Dunham. "Common subexpression processing in multiple-query processing." IEEE Transactions on Knowledge and Data Engineering 10, no. 3 (1998): 493–99. http://dx.doi.org/10.1109/69.687980.

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33

Ogasawara, Naomi, and Natasha Warner. "Processing missing vowels: Allophonic processing in Japanese." Language and Cognitive Processes 24, no. 3 (April 2009): 376–411. http://dx.doi.org/10.1080/01690960802084028.

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34

Kawamura, Satoru. "Effect of phonological processing on temporal processing." Japanese Psychological Research 42, no. 3 (September 2000): 178–82. http://dx.doi.org/10.1111/1468-5884.00143.

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35

Minhwa Chung and D. Moldevan. "Applying parallel processing to natural-language processing." IEEE Expert 9, no. 1 (February 1994): 36–44. http://dx.doi.org/10.1109/64.295133.

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36

Merigot, Alain, and Alfredo Petrosino. "Parallel processing for image and video processing." Parallel Computing 34, no. 12 (December 2008): 693. http://dx.doi.org/10.1016/j.parco.2008.09.001.

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37

Hansen, Jonathan C. "Processing negativity: Comparison process or selective processing?" Behavioral and Brain Sciences 13, no. 2 (June 1990): 242–43. http://dx.doi.org/10.1017/s0140525x0007850x.

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38

Dawson, Michael R. W., and Don P. Schopflocher. "Autonomous processing in parallel distributed processing networks." Philosophical Psychology 5, no. 2 (January 1992): 199–219. http://dx.doi.org/10.1080/09515089208573056.

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39

Jain, VK, JM Wills, and SA Wadekar. "Parallel processing architectures for advanced signal processing." Microprocessors and Microsystems 16, no. 9 (January 1992): 471–79. http://dx.doi.org/10.1016/0141-9331(92)90108-6.

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40

IKEDA, Masayuki. "Precision Processing by Laser. Laser Material Processing." Journal of the Japan Society for Precision Engineering 65, no. 11 (1999): 1539–42. http://dx.doi.org/10.2493/jjspe.65.1539.

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41

Yamashina, Masakazu. "Video Signal Processing LSI. Image Processing DSP." Journal of the Institute of Television Engineers of Japan 48, no. 1 (1994): 38–43. http://dx.doi.org/10.3169/itej1978.48.38.

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42

Hori, Takashi. "RTP (Rapid thermal Processing) technique." JOURNAL OF THE ILLUMINATING ENGINEERING INSTITUTE OF JAPAN 75, Appendix (1991): 239–40. http://dx.doi.org/10.2150/jieij1980.75.appendix_239.

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43

KOHDA, Toshitaka. "Information Processing." Journal of exercise physiology 4, no. 3 (1989): 105–9. http://dx.doi.org/10.1589/rika1986.4.105.

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44

O'Neill, P. "SEED PROCESSING." NZGA: Research and Practice Series 5 (January 1, 1990): 35–36. http://dx.doi.org/10.33584/rps.5.1998.3337.

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Анотація:

Co-operation, tolerance, communication and planning are necessary at harvest 1 time, and can help minimise delays and difficulties when off-loading seed at the processing plant. In normal circumstances the first areas of concern on the seed's arrival into store are the condition of the seed and the certification requirements. These areas have been dealt with in other papers, so this paper will concentrate on the post-harvest treatment of seed. A common fault in ryegrass harvesting is to. include a large amount of light trash, straw and empty glumes in the sample. This creates problems when dressing, for although the rubbish can be removed relatively easily and the weight loss may not be excessive, production from the plant is likely to be reduced because of the volume passing through the machine. Furthermore, in an effort not to lose good seed the operator may tend to cut back on 'blast'. This in turn may result in an inferior Purity and Germination test because of the inert matter content.

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45

Lee, CaraBeth. "Central Processing." Annals of Internal Medicine 170, no. 11 (June 4, 2019): 811. http://dx.doi.org/10.7326/m18-2339.

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46

Hirai, Toshio. "CVD Processing." MRS Bulletin 20, no. 1 (January 1995): 45–47. http://dx.doi.org/10.1557/s0883769400048946.

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Анотація:

Various methods are used in functionally gradient materials technology to control the composition and structure of a composite.The chemical vapor deposition (CVD) method yields a deposit with source gases by applying variou s forms of energy (heat, light, plasma, etc.) to the gases after they are introduced into a CVD reactor. Hydride, bromide, and chloride are generally used for source materials. By continually changing the mixture ratio of source gases or by controlling the CVD conditions such as deposition temperatures, gas pressure, and gas-flow rate, CVD permits relatively easy syntheses of various FGMs (to a maximum thickness on the order of a centimeter).

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47

Tamura, Satoshi. "Film Processing." Seikei-Kakou 27, no. 7 (June 20, 2015): 266–70. http://dx.doi.org/10.4325/seikeikakou.27.266.

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48

KANAI, Takashi. "Mesh Processing." Journal of the Japan Society for Precision Engineering 84, no. 4 (2018): 323–27. http://dx.doi.org/10.2493/jjspe.84.323.

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49

Arxiu, Revista. "Computer processing." Arxiu d'Etnografia de Catalunya, no. 4-5 (February 12, 2016): 106. http://dx.doi.org/10.17345/aec4-5.106-107.

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50

Künzel, Sebatian. "Processors Processing." CALICO Journal 12, no. 4 (January 14, 2013): 106–13. http://dx.doi.org/10.1558/cj.v12i4.106-113.

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