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Journal articles on the topic 'Sampling – Software'

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Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Lin Zuo, Lin Zuo, Lihui Feng Lihui Feng, Aiying Yang Aiying Yang, Junsen Lai Junsen Lai, and Yunan Sun Yunan Sun. "Experimental investigation on bit-rate-adaptive software synchronous optical sampling." Chinese Optics Letters 11, no. 5 (2013): 050603–50606. http://dx.doi.org/10.3788/col201311.050603.

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2

Lamperez, A. J., and S. T. Huang. "Software testing and sequential sampling." IEEE Journal on Selected Areas in Communications 12, no. 2 (1994): 302–5. http://dx.doi.org/10.1109/49.272880.

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3

Kaufman, Gordon M. "Successive sampling and software reliability." Journal of Statistical Planning and Inference 49, no. 3 (February 1996): 343–69. http://dx.doi.org/10.1016/0378-3758(96)85327-4.

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4

Sadeghi-Ba, H., K. Mohammad, S. Arshi, S. R. Majdzadeh, and S. Mohammadi. "Pilot Evaluation of the First Iranian Sampling Software for Health Research (Yasin Sampling Software)." Information Technology Journal 6, no. 1 (December 15, 2006): 135–41. http://dx.doi.org/10.3923/itj.2007.135.141.

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5

Thelin, Thomas, Håkan Petersson, Per Runeson, and Claes Wohlin. "Applying sampling to improve software inspections." Journal of Systems and Software 73, no. 2 (October 2004): 257–69. http://dx.doi.org/10.1016/s0164-1212(03)00249-8.

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6

Sonnaillon, Maximiliano O., Raúl Urteaga, and Fabián J. Bonetto. "Software PLL Based on Random Sampling." IEEE Transactions on Instrumentation and Measurement 59, no. 10 (October 2010): 2621–29. http://dx.doi.org/10.1109/tim.2009.2036459.

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7

Harshali, M., and M. Venu Gopala Rao. "Sub sampling based software GPS receiver." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 722. http://dx.doi.org/10.14419/ijet.v7i2.7.10931.

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This paper focuses on reducing the processing time of software GPS receiver using sub-sampling techniques. As the GPS signals are wide band signals, sampling frequency is very high. Sub-sampling enables to reduce time for processing. From the simulation results, it is observed that the sampling frequency can be reduced up to 2.5 MHz without loss of tracked signal. The processing time is reduced for software GPS receiver after sub-sampling. The overall reduction in processing time is from 3.456647 sec to 2.15946 sec respectively for sampling frequency 5 MHz , 2.5 MHz. Thus time saved is 37% of the original one.

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8

Tu, Yanbin, Min Lu, and Y. Alex Tung. "A study of software product sampling." International Journal of Technology Marketing 7, no. 3 (2012): 306. http://dx.doi.org/10.1504/ijtmkt.2012.048118.

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9

Podgurski, Andy, and Lynn Pierce. "Retrieving reusable software by sampling behavior." ACM Transactions on Software Engineering and Methodology 2, no. 3 (July 1993): 286–303. http://dx.doi.org/10.1145/152388.152392.

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10

Kirkham, C. C. "Ranked reservoir sampling: an extension to the reservoir sampling algorithm." Software: Practice and Experience 37, no. 12 (2007): 1285–88. http://dx.doi.org/10.1002/spe.805.

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11

ZHANG, De-Ping, Chang-Hai NIE, and Bao-Wen XU. "Importance Sampling Method of Software Reliability Estimation." Journal of Software 20, no. 10 (November 10, 2009): 2859–66. http://dx.doi.org/10.3724/sp.j.1001.2009.03553.

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12

Darão, Fernando, M. Teresa Carvalho, Ana Soares, and Elsa Agante. "MSWSampling - Software Tool for Solid Wastes Sampling." IFAC Proceedings Volumes 34, no. 18 (September 2001): 397–401. http://dx.doi.org/10.1016/s1474-6670(17)33240-8.

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13

Podgurski, Andy, Wassim Masri, Yolanda McCleese, Francis G. Wolff, and Charles Yang. "Estimation of software reliability by stratified sampling." ACM Transactions on Software Engineering and Methodology 8, no. 3 (July 1999): 263–83. http://dx.doi.org/10.1145/310663.310667.

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14

OKAMURA, Hiroyuki, and Tadashi DOHI. "Software Reliability Modeling Based on Capture-Recapture Sampling." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E92-A, no. 7 (2009): 1615–22. http://dx.doi.org/10.1587/transfun.e92.a.1615.

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15

Chan, F. T., T. Y. Chen, I. K. Mak, and Y. T. Yu. "Proportional sampling strategy: guidelines for software testing practitioners." Information and Software Technology 38, no. 12 (January 1996): 775–82. http://dx.doi.org/10.1016/0950-5849(96)01103-2.

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16

Lin Zuo, Lin Zuo, Aiying Yang Aiying Yang, Junsen Lai Junsen Lai, and Yunan Sun Yunan Sun. "Experimental investigation on a software synchronous optical sampling technique based on periodically poled lithium niobate." Chinese Optics Letters 10, no. 10 (2012): 100701–3. http://dx.doi.org/10.3788/col201210.100701.

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17

Palmer, Christopher R., and Christos Faloutsos. "Density biased sampling." ACM SIGMOD Record 29, no. 2 (June 2000): 82–92. http://dx.doi.org/10.1145/335191.335384.

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18

Westlund, M., H. Sunnerud, M. Karlsson, and P. A. Andrekson. "Software-synchronized all-optical sampling for fiber communication systems." Journal of Lightwave Technology 23, no. 3 (March 2005): 1088–99. http://dx.doi.org/10.1109/jlt.2004.838875.

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19

Seiffert, C., T. M. Khoshgoftaar, and J. Van Hulse. "Improving Software-Quality Predictions With Data Sampling and Boosting." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 39, no. 6 (November 2009): 1283–94. http://dx.doi.org/10.1109/tsmca.2009.2027131.

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20

Wagaman, John C. "Sampling distributions for introductory statistics students using internet polling software." International Journal of Mathematical Education in Science and Technology 44, no. 3 (April 15, 2013): 468–73. http://dx.doi.org/10.1080/0020739x.2012.729616.

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21

Arkesteijn, V. J., E. A. M. Klumperink, and B. Nauta. "Jitter requirements of the sampling clock in software radio receivers." IEEE Transactions on Circuits and Systems II: Express Briefs 53, no. 2 (February 2006): 90–94. http://dx.doi.org/10.1109/tcsii.2005.856893.

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22

Yoon, Seunghyun, Taejin Ha, Sunghwan Kim, and Hyuk Lim. "Scalable Traffic Sampling Using Centrality Measure on Software-Defined Networks." IEEE Communications Magazine 55, no. 7 (2017): 43–49. http://dx.doi.org/10.1109/mcom.2017.1600990.

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23

Gutjahr, Walter J. "Importance Sampling of Test Cases in Markovian Software Usage Models." Probability in the Engineering and Informational Sciences 11, no. 1 (January 1997): 19–36. http://dx.doi.org/10.1017/s0269964800004642.

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Recently, some authors have suggested usage models of Markov type as a technique of specifying the estimated operational use distribution of a given program. A main purpose of such models is the derivation of random test cases allowing unbiased estimates on the (un)reliability of the program in its intended environment. In this article, we show that by a shift of the transition probabilities of the Markov chain corresponding to such a model, prior information on the errorjproneness of single-program operations can be taken into account. An unbiased unreliability estimator with reduced variance is obtained. Furthermore, it is shown that minimization of the variance leads to a special stochastic optimization problem that can be demonstrated to be convex, such that efficient solution techniques apply. Some related questions are also treated in a more general, non-Markovian framework.

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24

Chen, Jianfeng, Vivek Nair, Rahul Krishna, and Tim Menzies. "“Sampling” as a Baseline Optimizer for Search-Based Software Engineering." IEEE Transactions on Software Engineering 45, no. 6 (June 1, 2019): 597–614. http://dx.doi.org/10.1109/tse.2018.2790925.

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25

Jeelani, M. Iqbal. "Application of Simple Random Sampling in Agriculture using R-software." Indian Journal of Science and Technology 4, no. 5 (May 20, 2014): 706–9. http://dx.doi.org/10.17485/ijst/2014/v7i5.18.

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26

Drown, D. J., T. M. Khoshgoftaar, and N. Seliya. "Evolutionary Sampling and Software Quality Modeling of High-Assurance Systems." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 39, no. 5 (September 2009): 1097–107. http://dx.doi.org/10.1109/tsmca.2009.2020804.

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27

Pan, Li-dong, and Fei Wang. "A software sampling frequency adaptive algorithm for reducing spectral leakage." Frontiers of Electrical and Electronic Engineering in China 1, no. 4 (December 2006): 375–79. http://dx.doi.org/10.1007/s11460-006-0072-6.

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28

Ha, Taejin, Sunghwan Kim, Namwon An, Jargalsaikhan Narantuya, Chiwook Jeong, JongWon Kim, and Hyuk Lim. "Suspicious traffic sampling for intrusion detection in software-defined networks." Computer Networks 109 (November 2016): 172–82. http://dx.doi.org/10.1016/j.comnet.2016.05.019.

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29

Dyer, Michael. "Distribution-based statistical sampling: An approach to software functional test." Journal of Systems and Software 20, no. 2 (February 1993): 107–14. http://dx.doi.org/10.1016/0164-1212(93)90002-f.

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30

Talbot, Christopher G., and Gordon Shaw. "Logic analyzer software for a multi-sampling E-beam prober." Microelectronic Engineering 12, no. 1-4 (May 1990): 65–72. http://dx.doi.org/10.1016/0167-9317(90)90016-m.

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31

Shen, Peng, Xiaoming Ding, Xuyun Mu, and Jianing Xu. "A software defect prediction method based on sampling and integration." Journal of Physics: Conference Series 1732 (January 2021): 012002. http://dx.doi.org/10.1088/1742-6596/1732/1/012002.

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32

Chaudhuri, Surajit, Rajeev Motwani, and Vivek Narasayya. "Random sampling for histogram construction." ACM SIGMOD Record 27, no. 2 (June 1998): 436–47. http://dx.doi.org/10.1145/276305.276343.

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33

Dimitrakakis, Christos, and Michail G. Lagoudakis. "Rollout sampling approximate policy iteration." Machine Learning 72, no. 3 (July 10, 2008): 157–71. http://dx.doi.org/10.1007/s10994-008-5069-3.

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34

Olken, Frank, Doron Rotem, and Ping Xu. "Random sampling from hash files." ACM SIGMOD Record 19, no. 2 (May 1990): 375–86. http://dx.doi.org/10.1145/93605.98746.

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35

Chaudhuri, Surajit, Rajeev Motwani, and Vivek Narasayya. "On random sampling over joins." ACM SIGMOD Record 28, no. 2 (June 1999): 263–74. http://dx.doi.org/10.1145/304181.304206.

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36

Wang, Yong, Xinbin Luo, Lu Ding, Shan Fu, and Shiqiang Hu. "Adaptive sampling for UAV tracking." Neural Computing and Applications 31, no. 9 (January 9, 2019): 5029–43. http://dx.doi.org/10.1007/s00521-018-03996-8.

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37

LIU, Wei. "A Graph-Based Approach for Web Database Sampling." Journal of Software 19, no. 2 (July 10, 2008): 179–93. http://dx.doi.org/10.3724/sp.j.1001.2008.00179.

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38

Bisbal, Jes�s, and Jane Grimson. "Consistent database sampling as a database prototyping approach." Journal of Software Maintenance and Evolution: Research and Practice 14, no. 6 (November 2002): 447–59. http://dx.doi.org/10.1002/smr.263.

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39

Kaltenecker, Christian, Alexander Grebhahn, Norbert Siegmund, and Sven Apel. "The Interplay of Sampling and Machine Learning for Software Performance Prediction." IEEE Software 37, no. 4 (July 2020): 58–66. http://dx.doi.org/10.1109/ms.2020.2987024.

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40

Sun, Zhongbin, Jingqi Zhang, Heli Sun, and Xiaoyan Zhu. "Collaborative filtering based recommendation of sampling methods for software defect prediction." Applied Soft Computing 90 (May 2020): 106163. http://dx.doi.org/10.1016/j.asoc.2020.106163.

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41

NISHIMURA, H., M. INAMORI, and Y. SANADA. "Sampling Rate Selection for Fractional Sampling in OFDM." IEICE Transactions on Communications E91-B, no. 9 (September 1, 2008): 2876–82. http://dx.doi.org/10.1093/ietcom/e91-b.9.2876.

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42

Yini Bao, and E. M. Bakker. "Content Based Web Sampling." International Journal of Digital Content Technology and its Applications 4, no. 1 (February 28, 2010): 43–68. http://dx.doi.org/10.4156/jdcta.vol4.issue1.6.

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43

Gabielkov, Maksym, Ashwin Rao, and Arnaud Legout. "Sampling online social networks." ACM SIGCOMM Computer Communication Review 44, no. 4 (February 25, 2015): 127–28. http://dx.doi.org/10.1145/2740070.2631452.

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44

Kett, James R. "Technology Tips: Teaching Sampling Distributions Using Autograph." Mathematics Teacher 105, no. 3 (October 2011): 226–29. http://dx.doi.org/10.5951/mathteacher.105.3.0226.

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45

CHEN, Jie. "Face Samples Expanding Based on the GA Re-Sampling." Journal of Software 16, no. 11 (2005): 1894. http://dx.doi.org/10.1360/jos161894.

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46

Conley, Harry, and Lou Fink. "Using Statistical Sampling." EDPACS 26, no. 12 (June 1999): 17. http://dx.doi.org/10.1201/1079/43240.26.12.19990601/30218.7.

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47

Lu, Wei, Yun Ling, Aiguo Song, Heng Zeng, Weimin Ding, Baoguo Xu, and Shipeng Gu. "Measuring Tape-Like Sampling Arm and Drill for Sampling Lunar Regolith." International Journal of Advanced Robotic Systems 10, no. 5 (January 2013): 239. http://dx.doi.org/10.5772/56361.

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48

Sandmann, W. "Efficiency of importance sampling estimators." Journal of Simulation 1, no. 2 (May 2007): 137–45. http://dx.doi.org/10.1057/palgrave.jos.4250011.

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49

Lipton, Richard J., Jeffrey F. Naughton, and Donovan A. Schneider. "Practical selectivity estimation through adaptive sampling." ACM SIGMOD Record 19, no. 2 (May 1990): 1–11. http://dx.doi.org/10.1145/93605.93611.

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50

Aumuller, Martin, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, and Francesco Silvestri. "Fair near neighbor search via sampling." ACM SIGMOD Record 50, no. 1 (June 15, 2021): 42–49. http://dx.doi.org/10.1145/3471485.3471496.

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Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. Given a set of points S and a radius parameter r > 0, the rnear neighbor (r-NN) problem asks for a data structure that, given any query point q, returns a point p within distance at most r from q. In this paper, we study the r-NN problem in the light of individual fairness and providing equal opportunities: all points that are within distance r from the query should have the same probability to be returned. In the low-dimensional case, this problem was first studied by Hu, Qiao, and Tao (PODS 2014). Locality sensitive hashing (LSH), the theoretically strongest approach to similarity search in high dimensions, does not provide such a fairness guarantee.

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