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Journal articles on the topic 'Data Processing - Optical Data Processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 July 2024

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1

Teller, J., F. Ozguner, and R. Ewing. "Data processing through optical interfaces." IEEE Aerospace and Electronic Systems Magazine 24, no. 10 (October 2009): 42–43. http://dx.doi.org/10.1109/maes.2009.5317786.

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2

Vâle, G., and A. Krûminsh. "Active Media for Optical Data Processing." Materials Science Forum 384-385 (January 2002): 329–32. http://dx.doi.org/10.4028/www.scientific.net/msf.384-385.329.

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3

Wu, Yarning, Liren Liu, and Zhijiang Wang. "Optical programmable shifting for data processing." Applied Optics 32, no. 26 (September 10, 1993): 4989. http://dx.doi.org/10.1364/ao.32.004989.

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4

Brenner, Karl-Heinz, and Adolf W. Lohmann. "Cyclic shifting for optical data processing." Applied Optics 27, no. 3 (February 1, 1988): 434. http://dx.doi.org/10.1364/ao.27.000434.

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5

Mehta, P. C. "Recent trends in optical data processing." Hyperfine Interactions 37, no. 1-4 (December 1987): 325–45. http://dx.doi.org/10.1007/bf02395719.

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6

NAGAE, Sadahiko. "Pattern Recognition by Optical Data Processing (3)." Journal of Graphic Science of Japan 20, no. 2 (1986): 7–13. http://dx.doi.org/10.5989/jsgs.20.2_7.

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7

MOTOYA, Yoshinobu. "Data Processing Employing an Optical Disk System." Zisin (Journal of the Seismological Society of Japan. 2nd ser.) 41, no. 3 (1988): 411–17. http://dx.doi.org/10.4294/zisin1948.41.3_411.

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8

Fateev, V. F., and A. P. Aleshkin. "Processing of multiple-site optical measurement data." Journal of Optical Technology 67, no. 7 (July 1, 2000): 634. http://dx.doi.org/10.1364/jot.67.000634.

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9

Kohler, D., M. Staehelin, and I. Zschokke-graenacher. "Organic Molecular Crystals for Optical Data Processing." Molecular Crystals and Liquid Crystals Science and Technology. Section A. Molecular Crystals and Liquid Crystals 229, no. 1 (May 1993): 117–22. http://dx.doi.org/10.1080/10587259308032184.

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10

Bräuchle, Ch, and N. Hampp. "The biopolymer bacteriorhodopsin in optical data processing." Makromolekulare Chemie. Macromolecular Symposia 50, no. 1 (October 1991): 97–105. http://dx.doi.org/10.1002/masy.19910500111.

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11

SHENG Lei, 盛磊, 吴志勇 WU Zhi-yong, 刘旨春 LIU Zhi-chun, 高策 Gao Ce, 张世学 ZHANG Shi-xue, and 王世刚 WANG Shi-gang. "Data processing for shipboard theodolite." Optics and Precision Engineering 21, no. 9 (2013): 2421–29. http://dx.doi.org/10.3788/ope.20132109.2421.

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12

Yegorov, A. D., V. A. Yegorov, S. A. Yegorov, and I. Ye Synelnikov. "IMPROVED METHODS OF DATA PROCESSING IN OPTICAL SPECTROMETERS." Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences 3, no. 1 (2019): 46–50. http://dx.doi.org/10.32838/2663-5941/2019.3-1/08.

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13

Yunlong, Zhang, Wang Zhibin, Zhang Feng, Guo Xiaogang, and Li Junqi. "Detection and data processing of diffractive optical element." Journal of Applied Optics 39, no. 3 (2018): 52–57. http://dx.doi.org/10.5768/jao201839.0302002.

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14

SUMARU, Kimio. "Optical Parallel Data Processing Using Organic Photochromic Materials." Kobunshi 50, no. 7 (2001): 460. http://dx.doi.org/10.1295/kobunshi.50.460.

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15

Polese, D., E. Martinelli, G. Magna, F. Dini, A. Catini, R. Paolesse, I. Lundstrom, and C. Di Natale. "Sharing data processing among replicated optical sensor arrays." Sensors and Actuators B: Chemical 179 (March 2013): 252–58. http://dx.doi.org/10.1016/j.snb.2012.10.032.

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16

Guest, Clark C., and Thomas K. Gaylord. "Phase stabilization system for holographic optical data processing." Applied Optics 24, no. 14 (July 15, 1985): 2140. http://dx.doi.org/10.1364/ao.24.002140.

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17

Collet, J. H., and M. Pugnet. "Picosecond Plasma Dynamics and All-Optical Data Processing." physica status solidi (b) 146, no. 1 (March 1, 1988): 393–401. http://dx.doi.org/10.1002/pssb.2221460142.

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18

Likhachev, Aleksey V., and Marina V. Tabanyukhova. "A new processing algorithm for photoelasticity method data." Vestnik Tomskogo gosudarstvennogo universiteta. Matematika i mekhanika, no. 79 (2022): 100–110. http://dx.doi.org/10.17223/19988621/79/9.

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The photoelasticity method is a reliable tool for studying the stress state of flat elements in building structures using the models made of optically sensitive materials. In this paper, the classical photoelasticity is considered. The experimental data obtained with the use of the method are presented as interferograms. A decoding procedure implies the obtaining of some normal and tangential stress values in the plane of the model. The polarization-projection installations that are used in optical methods are rather simple. However, the digital processing of the images obtained during the loaded model transmission requires high-intelligent software. Nowadays, national and international laboratories, working with polarization-optical methods, strive to develop digital photoelasticity. For some reasons, the authors of the presented work needed to develop their own algorithms for decoding experimental data of the photoelasticity method. This work is mainly devoted to a formulation of the problems to be solved. Some of them have already been solved, and the results obtained are presented here. The authors place special emphasis on the description of the algorithm for tracing of interference fringes based on the analysis of the image gradient.

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19

Chumak, A. V., A. A. Serga, and B. Hillebrands. "Magnonic crystals for data processing." Journal of Physics D: Applied Physics 50, no. 24 (May 23, 2017): 244001. http://dx.doi.org/10.1088/1361-6463/aa6a65.

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20

Tan Zhongwei, 谭中伟, 秦凤杰 Qin Fengjie, 任文华 Ren Wenhua, and 刘艳 Liu Yan. "Application of Fiber Dispersion in All Optical Data Processing." Laser & Optoelectronics Progress 50, no. 8 (2013): 080023. http://dx.doi.org/10.3788/lop50.080023.

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21

Wohlfeil, J., A. Börner, M. Buder, I. Ernst, D. Krutz, and R. Reulke. "REAL TIME DATA PROCESSING FOR OPTICAL REMOTE SENSING PAYLOADS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B5 (July 24, 2012): 63–68. http://dx.doi.org/10.5194/isprsarchives-xxxix-b5-63-2012.

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22

Tanida, Jun, and Yoshiki Ichioka. "Programming of optical array logic 1: Image data processing." Applied Optics 27, no. 14 (July 15, 1988): 2926. http://dx.doi.org/10.1364/ao.27.002926.

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23

Ewen, J. F., K. P. Jackson, R. J. S. Bates, and E. B. Flint. "GaAs fiber-optic modules for optical data processing networks." Journal of Lightwave Technology 9, no. 12 (1991): 1755–63. http://dx.doi.org/10.1109/50.108721.

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24

Pilipovich, V. A., A. K. Esman, I. A. Goncharenko, and V. K. Kuleshov. "Optical data switching in information processing and measuring systems." Measurement Techniques 47, no. 9 (September 2004): 879–83. http://dx.doi.org/10.1007/s11018-005-0034-z.

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25

Matoba, Osamu, and Bahram Javidi. "Secure Ultrafast Data Communication and Processing." Optics and Photonics News 13, no. 5 (May 1, 2002): 70. http://dx.doi.org/10.1364/opn.13.5.000070.

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26

Leenaerts, Domine M. W. "Data processing based on wave propagation." International Journal of Circuit Theory and Applications 27, no. 6 (November 1999): 633–45. http://dx.doi.org/10.1002/(sici)1097-007x(199911/12)27:6<633::aid-cta88>3.0.co;2-m.

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27

Li, Shuang, Shanchuan Liao, Wenjing Li, Luqun Li, and Dazhi Li. "Research on Key Technologies of Data Processing Mechanisms in Ternary Optical Computer." Applied Sciences 14, no. 13 (June 27, 2024): 5598. http://dx.doi.org/10.3390/app14135598.

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This paper introduces an arithmetic data file, a key technology for data processing in a ternary optical computer (TOC). The physical form of the ternary optical processor and its data processing characteristics are analyzed. Based on this analysis, the compution-data is constructed, and research is carried out on the format of the compution-data, its generation method, and the expansion of high-level languages transmitted to the ternary optical processor. The calculation rules and the raw data for the ternary optical computer are organized into a file that conforms to the calculation characteristics of the computer. A data processing mechanism based on the compution-data is proposed. Finally, an experimental test was conducted on the platform of a ternary optical computer using specific examples. The results showed that by organizing and transmitting data through the compution-data, the ternary optical computer could fully utilize its computational advantages in data processing while shielding the underlying complex hardware processing. This makes it convenient for users to apply this new type of computer. This data processing mechanism can offer a novel perspective for other heterogeneous systems in data processing.

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28

Manjunath, Akanksh Aparna, Manjunath Sudhakar Nayak, Santhanam Nishith, Satish Nitin Pandit, Shreyas Sunkad, Pratiba Deenadhayalan, and Shobha Gangadhara. "Automated invoice data extraction using image processing." IAES International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (June 1, 2023): 514. http://dx.doi.org/10.11591/ijai.v12.i2.pp514-521.

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Manually processing invoices which are in the form of scanned photocopies is a time-consuming process. There is a need to automate the task of extraction of data from the invoices with a similar format. In this paper we investigate and analyse various techniques of image processing and text extraction to improve the results of the optical character recognition (OCR) engine, which is applied to extract the text from the invoice. This paper also proposes the design and implementation of a web enabled invoice processing system (IPS). The IPS consists of an annotation tool and an extraction tool. The annotation tool is used to mark the fields of interest in the invoice which are to be extracted. The extraction tool makes use of opensource computer vision library (OpenCV) algorithms to detect text. The proposed system was tested on more than 25 types of invoices with the average accuracy score lying between 85% and 95%. Finally, to provide ease of use, a web application is developed which also presents the results in a structured format. The entire system is designed so as to provide flexibility and automate the process of extracting details of interest from the invoices.

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29

Bock, Rudolf K. "Data processing for bubble chambers." Nuclear Physics B - Proceedings Supplements 36 (July 1994): 229–40. http://dx.doi.org/10.1016/0920-5632(94)90775-7.

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30

Turitsyn, Sergei K., Jaroslaw E. Prilepsky, Son Thai Le, Sander Wahls, Leonid L. Frumin, Morteza Kamalian, and Stanislav A. Derevyanko. "Nonlinear Fourier transform for optical data processing and transmission: advances and perspectives." Optica 4, no. 3 (February 28, 2017): 307. http://dx.doi.org/10.1364/optica.4.000307.

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31

Vynnyk, Oleksandr, Yevheniia Butyrina, and Roman Kratenko. "VISUAL DATA COMPUTER PROCESSING IN EDUCATIONAL DIY PROJECTS." OPEN EDUCATIONAL E-ENVIRONMENT OF MODERN UNIVERSITY, no. 16 (2024): 1–21. http://dx.doi.org/10.28925/2414-0325.2024.161.

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The software tools for processing visual data in an educational chemical experiment, the experience of their usage, and a number of DIY (Do it yourself) projects developed on their basis were analyzed. Particular attention was paid to the role of self-made devices during the forced online education caused by COVID-19 and the full-scale war in Ukraine. The results of the development of the software tool ColorKit, which is being developed at the Department of Physics and Chemistry of H.S. Skovoroda Kharkiv National Pedagogical University are presented. The basic principles were covered, the interface was described, the main functions of the application and their areas of usage were given. The principle of operation of the modules: "Spectrophotometer", "Colorimeter", "Refractometer", "Polarimeter" was characterized. The features of the structure of optical computer devices for physico-chemical analysis developed by teachers, students of higher education and students, members of the Academy of Medical Sciences were considered, and the results of their testing were highlighted. The design of an absorption spectrophotometer based on a reflective diffraction grating made from a DVD disc was described; a new method of its calibration using a diamond green solution was proposed. The operating model was tested and it was established that the accuracy of the device was sufficient for demonstration and educational chemical experiments. The operating principle of the "Colorimeter" module of the ColorKit software tool was considered. It was shown that, unlike other software tools, it had built-in approximation tools, which significantly facilitated the processing of visual data; displaying the results of mathematical processing in a graphic form, which made the experiment visual. It should be noted that for the correct operation of the virtual spectrophotometer and colorimeter in real time, the correct setting of the video device driver is quite important. A number of optical schemes of refractometers developed on the basis of the ColorKit software tool were presented: with liquid and V-prisms; i.e. the device whose principle of action is based on changing the optical properties of the lens in contact with the solution. It was shown that the simultaneous display of the course of the rays and the results of mathematical processing provides a high level of visibility. The results of the approval of the LED DIE refractometer with a V-prism are outlined. Further prospects for the development of the ColorKit project are planned.

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32

Wnęk, Karol, and Piotr Boryło. "A Data Processing and Distribution System Based on Apache Nifi." Photonics 10, no. 2 (February 15, 2023): 210. http://dx.doi.org/10.3390/photonics10020210.

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The monitoring of physical and logical networks is essential for the high availability of 5G/6G networks. This could become a challenge in 5G/6G deployments due to the heterogeneity of the optical layer. It uses equipment from multiple vendors, and, as a result, the protocols and methods for gathering monitoring data usually differ. Simultaneously, to effectively support 5G/6G networks, the optical infrastructure should also be dense and ensure high throughput. Thus, vast numbers of photonic transceivers operating at up to 400 Gbps are needed to interconnect network components. In demanding optical solutions for 5G and beyond, enterprise-class equipment will be used—for example, high-capacity and high-density optical switches based on the SONiC distribution. These emerging devices produce vast amounts of data on the operational parameters of each optical transceiver, which should be effectively collected, processed, and analyzed. The aforementioned circumstances may lead to the necessity of using multiple independent monitoring systems dedicated to specific optical hardware. Apache NiFi can be used to address these potential issues. Its high configurability enables the aggregation of unstandardized log files collected from heterogenous devices. Furthermore, it is possible to configure Apache NiFi to absorb huge data streams about each of the thousands of transceivers comprising high-density optical switches. In this way, data can be preprocessed by using Apache NiFi and later uploaded to a dedicated system. In this paper, we focus on presenting the tool, its capabilities, and how it scales horizontally. The proven scalability is essential for making it usable in optical networks that support 5G/6G networks. Finally, we propose a unique optimization process that can greatly improve the performance and make Apache NiFi suitable for high-throughput and high-density photonic devices and optical networks. We also present some insider information on real-life implementations of Apache NiFi in commercial 5G networks that fully rely on optical networks.

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33

Xing, Mengdao, Zhong Lu, and Hanwen Yu. "InSAR Signal and Data Processing." Sensors 20, no. 13 (July 7, 2020): 3801. http://dx.doi.org/10.3390/s20133801.

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34

Wang, Jian. "Chip-scale optical interconnects and optical data processing using silicon photonic devices." Photonic Network Communications 31, no. 2 (July 23, 2015): 353–72. http://dx.doi.org/10.1007/s11107-015-0525-z.

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35

Tan Zhongqi, 谭中奇, 吴素勇 Wu Suyong, 刘贱平 Liu Jianping, 杨开勇 Yang Kaiyong, and 龙兴武 Long Xingwu. "Spectrum data processing in optical-feedback cavity ring-down spectroscopy." High Power Laser and Particle Beams 26, no. 10 (2014): 101006. http://dx.doi.org/10.3788/hplpb20142610.101006.

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36

Grigor'ev, A. N., A. I. Altuchov, and D. S. Korshunov. "An approach to photogrammetric processing of indirect optical location data." Scientific and Technical Journal of Information Technologies, Mechanics and Optics 21, no. 3 (June 1, 2021): 311–19. http://dx.doi.org/10.17586/2226-1494-2021-21-3-311-319.

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37

Kokodii, N. G., V. О. Timaniuk, E. Ya Levitin, and M. V. Kaydash. "ATTENUATION OF OPTICAL RADIATION BY NANOPARTICLES: ALGORITHM FOR DATA PROCESSING." Telecommunications and Radio Engineering 76, no. 10 (2017): 919–27. http://dx.doi.org/10.1615/telecomradeng.v76.i10.80.

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38

Wherrett, B. S., and S. D. Smith. "Bistable Semiconductor Elements for Optical Data Processing and Photonic Logic." Physica Scripta T13 (January 1, 1986): 189–94. http://dx.doi.org/10.1088/0031-8949/1986/t13/032.

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39

Watson, J., and G. Mackay. "Inspection of Integrated Circuit Photomasks using Optical Data Processing Techniques." Journal of Photographic Science 34, no. 1 (January 1986): 1–10. http://dx.doi.org/10.1080/00223638.1986.11738384.

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40

Nakamura, M., B. Leskovar, and B. Turko. "Signal processing for an optical wide band data transmission system." IEEE Transactions on Nuclear Science 35, no. 1 (1988): 197–204. http://dx.doi.org/10.1109/23.12706.

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41

Greated, Clive. "Optical methods and data processing in heat and fluid flow." Optics & Laser Technology 24, no. 5 (October 1992): 308. http://dx.doi.org/10.1016/0030-3992(92)90080-l.

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42

Zhang, Qiang, Xiaoying Liang, and Xiaopeng Wei. "Scattered Data Processing Approach Based on Optical Facial Motion Capture." Applied Bionics and Biomechanics 10, no. 2-3 (2013): 75–87. http://dx.doi.org/10.1155/2013/463235.

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In recent years, animation reconstruction of facial expressions has become a popular research field in computer science and motion capture-based facial expression reconstruction is now emerging in this field. Based on the facial motion data obtained using a passive optical motion capture system, we propose a scattered data processing approach, which aims to solve the common problems of missing data and noise. To recover missing data, given the nonlinear relationships among neighbors with the current missing marker, we propose an improved version of a previous method, where we use the motion of three muscles rather than one to recover the missing data. To reduce the noise, we initially apply preprocessing to eliminate impulsive noise, before our proposed three-order quasi-uniform B-spline-based fitting method is used to reduce the remaining noise. Our experiments showed that the principles that underlie this method are simple and straightforward, and it delivered acceptable precision during reconstruction.

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43

Petrov, V. V., A. A. Kryuchin, S. M. Shanoylo, and V. I. Sidorenko. "Optical Disks as a Basis of Modern Paperless Data Processing." Cybernetics and Systems Analysis 39, no. 5 (September 2003): 777–82. http://dx.doi.org/10.1023/b:casa.0000012098.70754.13.

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44

Bräuchle, C., and N. Hampp. "Optical Data Processing with Bacteriorhodopsin and its Genetically Modified Variants." Molecular Crystals and Liquid Crystals Science and Technology. Section A. Molecular Crystals and Liquid Crystals 216, no. 1 (June 1992): 43–48. http://dx.doi.org/10.1080/10587259208028747.

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45

Abushagur, Mustafa A. G. "Adaptive array radar data processing using the bimodal optical computer." Microwave and Optical Technology Letters 1, no. 7 (September 1988): 236–40. http://dx.doi.org/10.1002/mop.4650010704.

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46

Conway, T., R. Conway, and S. Tosi. "Signal processing for multitrack digital data storage." IEEE Transactions on Magnetics 41, no. 4 (April 2005): 1333–39. http://dx.doi.org/10.1109/tmag.2005.845394.

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47

Temma, T., M. Iwashita, K. Matsumoto, H. Kurokawa, and T. Nukiyama. "Data flow processor chip for image processing." IEEE Transactions on Electron Devices 32, no. 9 (September 1985): 1784–91. http://dx.doi.org/10.1109/t-ed.1985.22198.

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48

Odeberg, Hans. "A tactile sensor data-processing system." Sensors and Actuators A: Physical 49, no. 3 (July 1995): 173–80. http://dx.doi.org/10.1016/0924-4247(95)01030-0.

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49

Vershinin, Ye V., M. L. Prokofyev, and V. R. Afanasyev. "DEVELOPING FISCAL DATA PROCESSING ANALYTICAL SYSTEM." Issues of radio electronics, no. 3 (March 20, 2019): 78–82. http://dx.doi.org/10.21778/2218-5453-2019-3-78-82.

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The paper deals with the task of designing an analytical system for processing fiscal data. From a business point of view, such a system should solve the problem of analyzing a market basket, that is, finding the most typical patterns of purchases. From the point of view of data mining, the task of searching for association rules is solved, which consists of two stages: the search for all frequent sets with their support values and the acquisition of association rules based on the sets found. The first stage is provided by various search algorithms for frequent sets. In the paper, the algorithm chosen is the Frequent Pattern Growth Strategy (FPG) as the optimal one. The mathematical formulation of the task and the method for implementing the selected algorithm within the target system are given. The result of the work is a description of the fault‑tolerant and scalable model of the analytical system.

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50

Tobiška, Petr, and Jiří Homola. "Advanced data processing for SPR biosensors." Sensors and Actuators B: Chemical 107, no. 1 (May 2005): 162–69. http://dx.doi.org/10.1016/j.snb.2004.09.040.

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