Academic literature on the topic 'Data of variable size'
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Journal articles on the topic "Data of variable size"
Fibriyanti, Yenni Vera. "THE INFLUENCE OF CORPORATE GOVERNANCE, LEVERAGE, COMPANY SIZE ON FINANCIAL PERFORMANCE." JHSS (Journal of Humanities and Social Studies) 6, no. 3 (October 29, 2022): 345–48. http://dx.doi.org/10.33751/jhss.v6i3.6490.
Full textAxford, Danny, Robin Owen, and Gwyndaf Evans. "Diffraction data collection with a dynamically variable beam size." Acta Crystallographica Section A Foundations of Crystallography 69, a1 (August 25, 2013): s409. http://dx.doi.org/10.1107/s0108767313096438.
Full textNur Syamsiyah and Wulandari. "Factors Affecting Dividend Policy in Financial Sector Companies in Indonesia: Panel Data Analysis." JFBA: Journal of Financial and Behavioural Accounting 2, no. 1 (April 30, 2022): 35–45. http://dx.doi.org/10.33830/jfba.v2i1.3642.2022.
Full textMa, Yung-Cheng, Jih-Ching Chiu, Tien-Fu Chen, and Chung-Ping Chung. "Variable-size data item placement for load and storage balancing." Journal of Systems and Software 66, no. 2 (May 2003): 157–66. http://dx.doi.org/10.1016/s0164-1212(02)00073-0.
Full textMukherjee, Prasita, Sourasekhar Banerjee, and Asoke Nath. "Data Hiding Algorithm using Variable Block Size in Cover Image File." International Journal of Computer Applications 89, no. 13 (March 26, 2014): 11–20. http://dx.doi.org/10.5120/15690-4559.
Full textRizky, Zan Ana, and Anton Bawono. "THE EFFECT OF CAR, SIZE, CKPN, NPF ON FDR BUS WITH TPF AS INTERVENING VARIABLES IN 2016-2021." JOURNAL OF APPLIED MANAGERIAL ACCOUNTING 6, no. 2 (October 31, 2022): 221–32. http://dx.doi.org/10.30871/jama.v6i2.4076.
Full textAngraeni, Windy, Elvin Bastian, and Tri Lestari. "The Effect of Leverage, Firm Size, Profitability and Political Connections on Income Smoothing." Journal of Applied Business, Taxation and Economics Research 1, no. 6 (August 30, 2022): 532–35. http://dx.doi.org/10.54408/jabter.v1i6.93.
Full textWicaksono, Dimas, and Ade Saputra. "10.84389 Pengaruh Managerial Ownership, Profitability, Firm Size dan Capital Structure." AKRUAL : Jurnal Akuntansi dan Keuangan 5, no. 1 (August 15, 2023): 1–11. http://dx.doi.org/10.34005/akrual.v5i1.3061.
Full textZhao, Naifei, Qingsong Xu, Man-lai Tang, and Hong Wang. "Variable Screening for Near Infrared (NIR) Spectroscopy Data Based on Ridge Partial Least Squares Regression." Combinatorial Chemistry & High Throughput Screening 23, no. 8 (November 2, 2020): 740–56. http://dx.doi.org/10.2174/1386207323666200428114823.
Full textIndrabudiman, Amir. "Model and Financial Performance: Panel Data in Causality and Cointegration Test." International Journal of Engineering & Technology 7, no. 3.27 (August 15, 2018): 391. http://dx.doi.org/10.14419/ijet.v7i3.27.17979.
Full textDissertations / Theses on the topic "Data of variable size"
Chen, Haiying. "Ranked set sampling for binary and ordered categorical variables with applications in health survey data." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1092770729.
Full textTitle from first page of PDF file. Document formatted into pages; contains xiii, 109 p.; also includes graphics Includes bibliographical references (p. 99-102). Available online via OhioLINK's ETD Center
Liv, Per. "Efficient strategies for collecting posture data using observation and direct measurement." Doctoral thesis, Umeå universitet, Yrkes- och miljömedicin, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-59132.
Full textHögberg, Hans. "Some properties of measures of disagreement and disorder in paired ordinal data." Doctoral thesis, Örebro universitet, Handelshögskolan vid Örebro universitet, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-12350.
Full textStatistical methods for ordinal data
Fakhouri, Elie Michel. "Variable block-size motion estimation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ37260.pdf.
Full textRuengvirayudh, Pornchanok. "A Monte Carlo Study of Parallel Analysis, Minimum Average Partial, Indicator Function, and Modified Average Roots for Determining the Number of Dimensions with Binary Variables in Test Data: Impact of Sample Size and Factor Structure." Ohio University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou151516919677091.
Full textNataša, Krklec Jerinkić. "Line search methods with variable sample size." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2014. http://dx.doi.org/10.2298/NS20140117KRKLEC.
Full textU okviru ove teze posmatra se problem optimizacije bez ograničenja pri čcemu je funkcija cilja u formi matematičkog očekivanja. Očekivanje se odnosi na slučajnu promenljivu koja predstavlja neizvesnost. Zbog toga je funkcija cilja, u stvari, deterministička veličina. Ipak, odredjivanje analitičkog oblika te funkcije cilja može biti vrlo komplikovano pa čak i nemoguće. Zbog toga se za aproksimaciju često koristi uzoračko očcekivanje. Da bi se postigla dobra aproksimacija, obično je neophodan obiman uzorak. Ako pretpostavimo da se uzorak realizuje pre početka procesa optimizacije, možemo posmatrati uzoračko očekivanje kao determinističku funkciju. Medjutim, primena nekog od determinističkih metoda direktno na tu funkciju moze biti veoma skupa jer evaluacija funkcije pod ocekivanjem često predstavlja veliki trošak i uobičajeno je da se ukupan trošak optimizacije meri po broju izračcunavanja funkcije pod očekivanjem. Zbog toga su razvijeni metodi sa promenljivom veličinom uzorka. Većcina njih je bazirana na odredjivanju optimalne dinamike uvećanja uzorka.Glavni cilj ove teze je razvoj algoritma koji, kroz smanjenje broja izračcunavanja funkcije, smanjuje ukupne trošskove optimizacije. Ideja je da se veličina uzorka smanji kad god je to moguće. Grubo rečeno, izbegava se koriscenje velike preciznosti (velikog uzorka) kada smo daleko od rešsenja. U čcetvrtom poglavlju ove teze opisana je nova klasa metoda i predstavljena je analiza konvergencije. Dokazano je da je aproksimacija rešenja koju dobijamo bar toliko dobra koliko i za metod koji radi sa celim uzorkom sve vreme.Još jedna bitna karakteristika metoda koji su ovde razmatrani je primena linijskog pretražzivanja u cilju odredjivanja naredne iteracije. Osnovna ideja je da se nadje odgovarajući pravac i da se duž njega vršsi pretraga za dužzinom koraka koja će dovoljno smanjiti vrednost funkcije. Dovoljno smanjenje je odredjeno pravilom linijskog pretraživanja. U čcetvrtom poglavlju to pravilo je monotono što znači da zahtevamo striktno smanjenje vrednosti funkcije. U cilju jos većeg smanjenja troškova optimizacije kao i proširenja skupa pogodnih pravaca, u petom poglavlju koristimo nemonotona pravila linijskog pretraživanja koja su modifikovana zbog promenljive velicine uzorka. Takodje, razmatrani su uslovi za globalnu konvergenciju i R-linearnu brzinu konvergencije.Numerički rezultati su predstavljeni u šestom poglavlju. Test problemi su razliciti - neki od njih su akademski, a neki su realni. Akademski problemi su tu da nam daju bolji uvid u ponašanje algoritama. Sa druge strane, podaci koji poticu od stvarnih problema služe kao pravi test za primenljivost pomenutih algoritama. U prvom delu tog poglavlja akcenat je na načinu ažuriranja veličine uzorka. Različite varijante metoda koji su ovde predloženi porede se medjusobno kao i sa drugim šemama za ažuriranje veličine uzorka. Drugi deo poglavlja pretežno je posvećen poredjenju različitih pravila linijskog pretraživanja sa različitim pravcima pretraživanja u okviru promenljive veličine uzorka. Uzimajuci sve postignute rezultate u obzir dolazi se do zaključcka da variranje veličine uzorka može značajno popraviti učinak algoritma, posebno ako se koriste nemonotone metode linijskog pretraživanja.U prvom poglavlju ove teze opisana je motivacija kao i osnovni pojmovi potrebni za praćenje preostalih poglavlja. U drugom poglavlju je iznet pregled osnova nelinearne optimizacije sa akcentom na metode linijskog pretraživanja, dok su u trećem poglavlju predstavljene osnove stohastičke optimizacije. Pomenuta poglavlja su tu radi pregleda dosadašnjih relevantnih rezultata dok je originalni doprinos ove teze predstavljen u poglavljima 4-6.
Hintze, Christopher Jerry. "Modeling correlation in binary count data with application to fragile site identification." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4278.
Full textSodagari, Shabnam. "Variable block-size disparity estimation in stereo imagery." Thesis, University of Ottawa (Canada), 2003. http://hdl.handle.net/10393/26399.
Full textDziminski, Martin A. "The evolution of variable offspring provisioning." University of Western Australia, 2005. http://theses.library.uwa.edu.au/adt-WU2005.0134.
Full textAcuna, Stamp Annabelen. "Design Study for Variable Data Printing." University of Cincinnati / OhioLINK, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=ucin962378632.
Full textBooks on the topic "Data of variable size"
Tritton, Kelvin. Variable data printing. Leatherhead: PIRA, 2003.
Find full textComponents, Philips. Variable capacitors: Data handbook. London: Philips Components, 1993.
Find full textChristine, Bachrach, National Survey of Family Growth (U.S.), and National Center for Health Statistics (U.S.), eds. National survey of family growth, cycle III: Sample design, weighting, and variance estimation : this report describes the procedures used to select the sample. Hyattsville, Md: U.S. Dept. of Health and Human Services, Public Health Service, National Center for Health Statistics, 1985.
Find full textSalomon, David. Variable-length Codes for Data Compression. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-959-0.
Full textAlbert, Boggess, and Stewart James 1941-, eds. Single variable CalcLabs with Derive: For Stewart's fourth edition, Calculus, Single variable calculus, Calculus--early transcendentals, Single variable calculus--early transcendentals. Pacific Grove, CA: Brooks/Cole Pub., 1999.
Find full textThomas' calculus: Single variable. Harlow: Addison-Wesley, 2009.
Find full textCenter, Goddard Space Flight, ed. Nickel-cadmium cell design variable program data analysis. Greenbelt, MD: National Aeronautics and Space Administration, Goddard Space Flight Center, 1985.
Find full textHirsch and Coxford. Predicting from Data: An alternative unit for representing and analyzing two-variable data. New York, NY: McGraw-Hill/Glencoe, 1995.
Find full textBizon, Thomas P. Real-time transmission of digital video using variable-lengthbcoding. [Washington, DC: National Aeronautics and Space Administration, 1993.
Find full textBizon, Thomas P. Real-time transmission of digital video using variable-lengthbcoding. [Washington, DC: National Aeronautics and Space Administration, 1993.
Find full textBook chapters on the topic "Data of variable size"
Quicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Count data as response variable." In Practical R for biologists: an introduction, 147–54. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0012.
Full textQuicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Count data as response variable." In Practical R for biologists: an introduction, 147–54. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0147.
Full textDjebour, Lamia, Reza Akbarinia, and Florent Masseglia. "Variable-Size Segmentation for Time Series Representation." In Transactions on Large-Scale Data- and Knowledge-Centered Systems LIII, 34–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-66863-4_2.
Full textPutluri, Srinivasareddy, and Md Zia Ur Rahman. "Novel Exon Predictors Using Variable Step Size Adaptive Algorithms." In Innovative Data Communication Technologies and Application, 750–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38040-3_86.
Full textBehera, Mandakini Priyadarshani, Archana Sarangi, Debahuti Mishra, and Srikanta Kumar Mohapatra. "Variable Step Size Firefly Algorithm for Automatic Data Clustering." In Smart Innovation, Systems and Technologies, 243–53. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9873-6_22.
Full textLi, Yuxiong, Yujuan Tan, Congcong Xu, Duo Liu, Xianzhang Chen, Chengliang Wang, Mingliang Zhou, and Leong Hou U. "AIR Cache: A Variable-Size Block Cache Based on Fine-Grained Management Method." In Web and Big Data, 158–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85899-5_12.
Full textDröge, Gisbert, and Hans-Jörg Schek. "Query- adaptive data space partitioning using variable-size storage clusters." In Advances in Spatial Databases, 337–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56869-7_19.
Full textLeirens, Sylvain, Christophe Villien, and Bruno Flament. "Feasibility of WiFi Site-Surveying Using Crowdsourced Data." In Latent Variable Analysis and Signal Separation, 479–88. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53547-0_45.
Full textQuicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Analysis of covariance (ANCOVA)." In Practical R for biologists: an introduction, 166–70. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0014.
Full textQuicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Analysis of covariance (ANCOVA)." In Practical R for biologists: an introduction, 166–70. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0166.
Full textConference papers on the topic "Data of variable size"
Wang, Su, and Chein-I. Chang. "Variable-size variable-band selection for spectral feature characterization in hyperspectral data." In Optics East 2006, edited by Steven D. Christesen, Arthur J. Sedlacek III, James B. Gillespie, and Kenneth J. Ewing. SPIE, 2006. http://dx.doi.org/10.1117/12.684911.
Full textKatsipoulakis, Nikos R., Alexandros Labrinidis, and Panos K. Chrysanthis. "Concept-Driven Load Shedding: Reducing Size and Error of Voluminous and Variable Data Streams." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622265.
Full textVoigt, Michael. "Watermarking geographic vector-data using a variable strip-size scheme." In Electronic Imaging 2007. SPIE, 2007. http://dx.doi.org/10.1117/12.704557.
Full textEmlek, Alper, Murat Peker, and Kamil Fatih Dilaver. "Variable window size for stereo image matching based on edge information." In 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017. http://dx.doi.org/10.1109/idap.2017.8090229.
Full textDo, Jaeyoung, Chen Luo, and David Lomet. "Programming an SSD Controller to Support Batched Writes for Variable-Size Pages." In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 2021. http://dx.doi.org/10.1109/icde51399.2021.00071.
Full textRusu, Alexandru-George, Laura-Maria Dogariu, Ruxandra-Liana Costea, Constantin Paleologu, Jacob Benesty, and Silviu Ciochina. "A Variable Step-Size Affine Projection Algorithm Based on Data Reuse." In 2022 45th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2022. http://dx.doi.org/10.1109/tsp55681.2022.9851279.
Full textWu, Cen, Wei Zhang, Yao Wang, and Chao Gao. "Study on the Performance of the Variable Step-Size LMS Algorithms." In 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA). IEEE, 2020. http://dx.doi.org/10.1109/iciba50161.2020.9276956.
Full textAzad, A. K. M., and J. Kamruzzaman. "Asynchronous Variable Hop Size Transmission with Stochastic Data Model for Sensor Networks." In 2008 IEEE International Conference on Communications. IEEE, 2008. http://dx.doi.org/10.1109/icc.2008.801.
Full textSzadkowski, Zbigniew. "Variable Step-Size Least Mean Square Filter Supressing Radio Frequency Interferentions in Cosmic Rays Radio Detection." In 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD). IEEE, 2018. http://dx.doi.org/10.1109/icabcd.2018.8465415.
Full textLi, Haiqing, and Lang Wang. "A variable size sliding window based frequent itemsets mining algorithm in data stream." In MATERIALS SCIENCE, ENERGY TECHNOLOGY, AND POWER ENGINEERING I: 1st International Conference on Materials Science, Energy Technology, Power Engineering (MEP 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.4982511.
Full textReports on the topic "Data of variable size"
Skone, Timothy J. Variable Size Wind Farm, Operation. Office of Scientific and Technical Information (OSTI), November 2010. http://dx.doi.org/10.2172/1509463.
Full textKim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1806.
Full textUechi, Luis, and José A. Barbero. Assessment of Transport Data Availability and Quality in Latin America. Inter-American Development Bank, January 2012. http://dx.doi.org/10.18235/0010453.
Full textKimhi, Ayal, Barry Goodwin, Ashok Mishra, Avner Ahituv, and Yoav Kislev. The dynamics of off-farm employment, farm size, and farm structure. United States Department of Agriculture, September 2006. http://dx.doi.org/10.32747/2006.7695877.bard.
Full textAxenrot, Thomas, Erik Degerman, and Anders Asp. Seasonal variation in thermal habitat volume for cold-water fish populations : implications for hydroacoustic survey design and stock assessment. Department of Aquatic Resources, Swedish University of Agricultural Sciences, 2023. http://dx.doi.org/10.54612/a.5i05rb1iu1.
Full textNelson, Gena, Hannah Carter, and Peter Boedeker. Early Math Interventions in Informal Learning Settings Coding Protocol. Boise State University, Albertsons Library, November 2021. http://dx.doi.org/10.18122/sped141.boisestate.
Full textAboal, Diego, and Paula Garda. Technological and Nontechnological Innovation and Productivity in Services vis a vis Manufacturing in Uruguay. Inter-American Development Bank, December 2012. http://dx.doi.org/10.18235/0006944.
Full textBernard, David Rhys, Gharad Bryan, Sylvain Chabé-Ferret, Jon de Quidt, Jasmin Claire Fliegner, and Roland Rathelot. How Biased are Observational Methods in Practice? Accumulating Evidence Using Randomised Controlled Trials with Imperfect Compliance. Centre for Excellence and Development Impact and Learning (CEDIL), April 2023. http://dx.doi.org/10.51744/crpp9.
Full textCampi, Mercedes, Marco Dueñas, and Tommaso Ciarli. Open configuration options Do Creative Industries Enhance Employment Growth? Regional Evidence from Colombia. Inter-American Development Bank, February 2022. http://dx.doi.org/10.18235/0003993.
Full textScholz, Florian. Sedimentary fluxes of trace metals, radioisotopes and greenhouse gases in the southwestern Baltic Sea Cruise No. AL543, 23.08.2020 – 28.08.2020, Kiel – Kiel - SEDITRACE. GEOMAR Helmholtz Centre for Ocean Research Kiel, November 2020. http://dx.doi.org/10.3289/cr_al543.
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