Relevant bibliographies by topics / Sampling – Software

Academic literature on the topic 'Sampling – Software'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Sampling – Software"

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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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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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Sampling – Software"

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Narayanappa, Harish B. "Monitoring software using property-aware program sampling." [Ames, Iowa : Iowa State University], 2010. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1476328.

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奚永忻 and Yung-shing Paul Hsi. "On proportional sampling strategies in software testing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B3122443X.

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Hsi, Yung-shing Paul. "On proportional sampling strategies in software testing." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22713293.

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Sun, Yi-Ran. "Generalized Bandpass Sampling Receivers for Software Defined Radio." Doctoral thesis, Stockholm, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4009.

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Sandoval, Alcocer Juan. "Horizontal profiling: A sampling technique to identify performance regressions." Tesis, Universidad de Chile, 2016. http://repositorio.uchile.cl/handle/2250/143666.

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Doctor en Ciencias, Mención Computación
Los cambios continuos en el código fuente de un programa pueden inadvertidamente introducir una regresión de rendimiento en tiempo de ejecución. Dichas regresiones se refieren a situaciones donde el rendimiento de un programa se degrada en comparación de versiones anteriores del mismo, aunque la nueva versión funcione correctamente. Ejecutar puntos de referencia en cada versión de un programa es una técnica tradicional utilizada para identificar regresiones en etapas tempranas. A pesar de ser efectiva, esta técnica exhaustiva es difícil de llevar a cabo en la práctica, principalmente por la alta sobrecarga que esta actividad demanda. En esta tesis, realizamos un estudio empírico sobre una variedad de programas, con el fin de evaluar cómo el rendimiento de un programa evoluciona en el tiempo, a medida que es modificado. Guiados por este estudio, proponemos Horizontal Profiling, una técnica de muestreo para inferir si una nueva versión de un programa introduce una variación de rendimiento, usando información de la ejecución de versiones anteriores. El objetivo de Horizontal Profiling es reducir la sobrecarga que requiere monitorear el rendimiento de cada versión, ejecutando los puntos de referencia solo en las versiones que contengan cambios costosos de código fuente. Presentamos una evaluación en la cual aplicamos Horizontal Profiling para identificar regresiones de rendimiento en un número de programas escritos en en el lenguaje de programación Pharo. En base a las aplicaciones que analizamos, encontramos que Horizontal Profiling es capaz de detectar más del 80% de las regresiones de rendimiento, ejecutando los puntos de referencia en menos del 20% de las versiones. Adicionalmente, describimos los patrones identificados durante nuestro estudio empírico, y detallamos cómo abordamos los numerosos desafíos que enfrentamos para completar nuestros experimentos.
Este trabajo ha sido parcialmente financiado por CONICYT a través de la beca CONICYT-PCHA/Doctorado Nacional para extranjeros/2013-63130199, OBJECT PROFILE y LAM RESEARCH
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Patel, Milan. "Investigations in bandpass sampling for wireless communications and software defined radio." Thesis, University College London (University of London), 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412490.

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Yip, Wang. "Towards a proportional sampling strategy according to path complexity a simulation study /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B22713232.

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Yip, Wang, and 葉弘. "Towards a proportional sampling strategy according to path complexity: a simulation study." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31225500.

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Kolsmyr, Johan, and Andreas Löfberg. "Software enhancement for improving sampling frequency and BLE communication in an embedded system." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-30928.

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Staunton, Richard C. "Visual inspection : image sampling, algorithms and architectures." Thesis, University of Warwick, 1991. http://wrap.warwick.ac.uk/108898/.

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The thesis concerns the hexagonal sampling of images, the processing of industrially derived images, and the design of a novel processor element that can be assembled into pipelines to effect fast, economic and reliable processing. A hexagonally sampled two dimensional image can require 13.4% fewer sampling points than a square sampled equivalent. The grid symmetry results in simpler processing operators that compute more efficiently than square grid operators. Computation savings approaching 44% arc demonstrated. New hexagonal operators arc reported including a Gaussian smoothing filter, a binary thinner, and an edge detector with comparable accuracy to that of the Sobel detector. The design of hexagonal arrays of sensors is considered. Operators requiring small local areas of support are shown to be sufficient for processing controlled lighting and industrial images. Case studies show that small features in hexagonally processed images maintain their shape better, and that processes can tolerate a lower signal to noise ratio, than that for equivalent square processed images. The modelling of small defects in surfaces has been studied in depth. The flexible programmable processor element can perform the low level local operators required for industrial image processing on both square and hexagonal grids. The element has been specified and simulated by a high level computer program. A fast communication channel allows for dynamic reprogramming by a control computer, and the video rate element can be assembled into various pipeline architectures, that may eventually be adaptively controlled.
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Books on the topic "Sampling – Software"

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McGuire, Sam. Audio sampling: A practical guide. Amsterdam: Focal Press, 2008.

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Venosa, Elettra. Software radio: Sampling rate selection, design and synchronization. New York: Springer Verlag, 2012.

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Music technology and the project studio: Sampling and synthesis. New York: Routledge, 2012.

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McGuire, Sam. Software sampling: A step-by-step guide to creating your own sampled instruments. Burlington, MA: Focal Press, 2008.

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Sparks, Anita. Sediment sampling application: User instructions : R:Base version 1.2. [Olympia, Wash.]: Northwest Indian Fisheries Commission, 1994.

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Classical and adaptive clinical trial designs with ExpDesign Studio? Hoboken, N.J: John Wiley, 2008.

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Adaptive design theory and implementation using SAS and R. Boca Raton: CRC Press, 2014.

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Chang, Mark. Adaptive design theory and implementation using SAS and R. Boca Raton, FL: CRC Press, 2007.

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Adaptive design theory and implementation using SAS and R. Boca Raton: Taylor & Francis, 2008.

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Sampling and Soft Synth Power! Thomson Course Technology, 2005.

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Book chapters on the topic "Sampling – Software"

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Tu, Yanbin, and Min Lu. "Modeling Dynamic Software Sampling Strategies." In Marketing, Technology and Customer Commitment in the New Economy, 216. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11779-9_76.

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Venosa, Elettra, fredric j. harris, and Francesco A. N. Palmieri. "Sampling Rate Selection, Timing Jitter and Time Interleaved ADCs." In Software Radio, 7–51. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0113-1_2.

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Mondin, Marina, Letizia Lo Presti, and Massimiliano Laddomada. "An Efficient Frequency Sampling Design of FIR Raised-Cosine Filters for Software Radio Applications." In Software Radio, 357–67. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0343-1_30.

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Chang, Fay, Keith I. Farkas, and Parthasarathy Ranganathan. "Energy-Driven Statistical Sampling: Detecting Software Hotspots." In Power-Aware Computer Systems, 110–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36612-1_8.

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Jegourel, Cyrille, Kim G. Larsen, Axel Legay, Marius Mikučionis, Danny Bøgsted Poulsen, and Sean Sedwards. "Importance Sampling for Stochastic Timed Automata." In Dependable Software Engineering: Theories, Tools, and Applications, 163–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47677-3_11.

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Pittou, Maria, and Stavros Tripakis. "Checking Multi-view Consistency of Discrete Systems with Respect to Periodic Sampling Abstractions." In Formal Aspects of Component Software, 73–91. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57666-4_6.

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Kimura, Mitsuhiro, and Takaji Fujiwara. "A New Criterion for the Optimal Software Release Problems: Moving Average Quality Control Chart with Bootstrap Sampling." In Advances in Software Engineering, 280–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10619-4_34.

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Balogun, Abdullateef O., Fatimah B. Lafenwa-Balogun, Hammed A. Mojeed, Fatimah E. Usman-Hamza, Amos O. Bajeh, Victor E. Adeyemo, Kayode S. Adewole, and Rasheed G. Jimoh. "Data Sampling-Based Feature Selection Framework for Software Defect Prediction." In International Conference on Emerging Applications and Technologies for Industry 4.0 (EATI’2020), 39–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80216-5_4.

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Deng, Jun, He Cai, and Xiaofei Wang. "Improved Flow Awareness by Intelligent Collaborative Sampling in Software Defined Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 182–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17513-9_13.

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Hossen, Md Anwar, Md Shariful Islam, Nurhafizah Abu Talip Yusof, Md Sakib Rahman, Fatema Siddika, Mostafijur Rahman, Sabira Khatun, Mohamad Shaiful Abdul Karim, and S. M. Hasan Mahmud. "Hybrid Sampling and Random Forest Based Machine Learning Approach for Software Defect Prediction." In Lecture Notes in Electrical Engineering, 541–53. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2317-5_46.

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Conference papers on the topic "Sampling – Software"

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Drongowski, Paul, Lei Yu, Frank Swehosky, Suravee Suthikulpanit, and Robert Richter. "Incorporating Instruction-Based Sampling into AMD CodeAnalyst." In Software (ISPASS). IEEE, 2010. http://dx.doi.org/10.1109/ispass.2010.5452049.

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Padilla, Gerardo, Carlos De Oca, I.-ling Yen, and Farokh Bastani. "Weighted Proportional Sampling : AGeneralization for Sampling Strategies in Software Testing." In 2006 3rd International Conference on Electrical and Electronics Engineering. IEEE, 2006. http://dx.doi.org/10.1109/iceee.2006.251865.

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de Mello, Rafael Maiani, Pedro Correa da Silva, and Guilherme Horta Travassos. "Sampling improvement in software engineering surveys." In the 8th ACM/IEEE International Symposium. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2652524.2652566.

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Zhang, Hongyu, and Rongxin Wu. "Sampling program quality." In 2010 IEEE 26th International Conference on Software Maintenance (ICSM). IEEE, 2010. http://dx.doi.org/10.1109/icsm.2010.5609671.

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Heidari, Sanaz, Hamid Mousavi, and Ali Movaghar. "On the Uniform Sampling of the Web: An Improvement on Bucket Based Sampling." In 2009 International Conference on Communication Software and Networks. IEEE, 2009. http://dx.doi.org/10.1109/iccsn.2009.164.

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Sira, Martin, Stanislav Maslan, and Vera Novakova Zachovalova. "QWTB — Software tool box for sampling measurements." In 2016 Conference on Precision Electromagnetic Measurements (CPEM 2016). IEEE, 2016. http://dx.doi.org/10.1109/cpem.2016.7540599.

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Palmieri, F., E. Venosa, A. Petropulu, G. Romano, and P. Salvo Rossi. "Sparse sampling for Software Defined Radio receivers." In 2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2010). IEEE, 2010. http://dx.doi.org/10.1109/spawc.2010.5671084.

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Lukin, Konstantin A., and Julia A. Shiyan. "Sampling rate reduction in Software Noise Radar." In 2008 International Radar Symposium (IRS). IEEE, 2008. http://dx.doi.org/10.1109/irs.2008.4585752.

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Kaltenecker, Christian, Alexander Grebhahn, Norbert Siegmund, Jianmei Guo, and Sven Apel. "Distance-Based Sampling of Software Configuration Spaces." In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE). IEEE, 2019. http://dx.doi.org/10.1109/icse.2019.00112.

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ZHUO, Hongyan, Chengliang GE, Zhiqiang LIU, and Jiaru ZHANG. "Applications of Timer of Data Sampling Software." In 2017 International Conference on Electronic Industry and Automation (EIA 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/eia-17.2017.31.

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Reports on the topic "Sampling – Software"

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Gaugush, Robert F. Sampling Design Software User's Manual. Fort Belvoir, VA: Defense Technical Information Center, February 1993. http://dx.doi.org/10.21236/ada262632.

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Akos, Dennis M., and Per Enge. GPS Software Radio. Direct RF Sampling Research. Fort Belvoir, VA: Defense Technical Information Center, May 2002. http://dx.doi.org/10.21236/ada405448.

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Bate, Lisa J., Torolf R. Torgersen, Michael J. Wisdom, Edward O. Garton, and Shawn C. Clabough. Log sampling methods and software for stand and landscape analyses. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2008. http://dx.doi.org/10.2737/pnw-gtr-746.

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Wyss, G. D., and K. H. Jorgensen. A user`s guide to LHS: Sandia`s Latin Hypercube Sampling Software. Office of Scientific and Technical Information (OSTI), February 1998. http://dx.doi.org/10.2172/573301.

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Swiler, Laura Painton, and Gregory Dane Wyss. A user's guide to Sandia's latin hypercube sampling software : LHS UNIX library/standalone version. Office of Scientific and Technical Information (OSTI), July 2004. http://dx.doi.org/10.2172/919175.

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Dols, W. Stuart, Brett D. Matzke, Landon H. Sego, Jayne B. Morrow, Lisa L. Nuffer, Brent A. Pulsipher, and Andrew K. Persily. Development and demonstration of a method to evaluate bio-sampling strategies using building simulation and sample planning software. Gaithersburg, MD: National Institute of Standards and Technology, 2009. http://dx.doi.org/10.6028/nist.tn.1636.

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McCarthy, Noel, Eileen Taylor, Martin Maiden, Alison Cody, Melissa Jansen van Rensburg, Margaret Varga, Sophie Hedges, et al. Enhanced molecular-based (MLST/whole genome) surveillance and source attribution of Campylobacter infections in the UK. Food Standards Agency, July 2021. http://dx.doi.org/10.46756/sci.fsa.ksj135.

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This human campylobacteriosis sentinel surveillance project was based at two sites in Oxfordshire and North East England chosen (i) to be representative of the English population on the Office for National Statistics urban-rural classification and (ii) to provide continuity with genetic surveillance started in Oxfordshire in October 2003. Between October 2015 and September 2018 epidemiological questionnaires and genome sequencing of isolates from human cases was accompanied by sampling and genome sequencing of isolates from possible food animal sources. The principal aim was to estimate the contributions of the main sources of human infection and to identify any changes over time. An extension to the project focussed on antimicrobial resistance in study isolates and older archived isolates. These older isolates were from earlier years at the Oxfordshire site and the earliest available coherent set of isolates from the national archive at Public Health England (1997/8). The aim of this additional work was to analyse the emergence of the antimicrobial resistance that is now present among human isolates and to describe and compare antimicrobial resistance in recent food animal isolates. Having identified the presence of bias in population genetic attribution, and that this was not addressed in the published literature, this study developed an approach to adjust for bias in population genetic attribution, and an alternative approach to attribution using sentinel types. Using these approaches the study estimated that approximately 70% of Campylobacter jejuni and just under 50% of C. coli infection in our sample was linked to the chicken source and that this was relatively stable over time. Ruminants were identified as the second most common source for C. jejuni and the most common for C. coli where there was also some evidence for pig as a source although less common than ruminant or chicken. These genomic attributions of themselves make no inference on routes of transmission. However, those infected with isolates genetically typical of chicken origin were substantially more likely to have eaten chicken than those infected with ruminant types. Consumption of lamb’s liver was very strongly associated with infection by a strain genetically typical of a ruminant source. These findings support consumption of these foods as being important in the transmission of these infections and highlight a potentially important role for lamb’s liver consumption as a source of Campylobacter infection. Antimicrobial resistance was predicted from genomic data using a pipeline validated by Public Health England and using BIGSdb software. In C. jejuni this showed a nine-fold increase in resistance to fluoroquinolones from 1997 to 2018. Tetracycline resistance was also common, with higher initial resistance (1997) and less substantial change over time. Resistance to aminoglycosides or macrolides remained low in human cases across all time periods. Among C. jejuni food animal isolates, fluoroquinolone resistance was common among isolates from chicken and substantially less common among ruminants, ducks or pigs. Tetracycline resistance was common across chicken, duck and pig but lower among ruminant origin isolates. In C. coli resistance to all four antimicrobial classes rose from low levels in 1997. The fluoroquinolone rise appears to have levelled off earlier and among animals, levels are high in duck as well as chicken isolates, although based on small sample sizes, macrolide and aminoglycoside resistance, was substantially higher than for C. jejuni among humans and highest among pig origin isolates. Tetracycline resistance is high in isolates from pigs and the very small sample from ducks. Antibiotic use following diagnosis was relatively high (43.4%) among respondents in the human surveillance study. Moreover, it varied substantially across sites and was highest among non-elderly adults compared to older adults or children suggesting opportunities for improved antimicrobial stewardship. The study also found evidence for stable lineages over time across human and source animal species as well as some tighter genomic clusters that may represent outbreaks. The genomic dataset will allow extensive further work beyond the specific goals of the study. This has been made accessible on the web, with access supported by data visualisation tools.
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