Relevant bibliographies by topics / Stratified sampling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Stratified sampling'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Stratified sampling"

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Mandal, B. N., Rajender Parsad, V. K. Gupta, and U. C. Sud. "Nested stratified sampling." Model Assisted Statistics and Applications 3, no. 3 (2008): 211–23. http://dx.doi.org/10.3233/mas-2008-3305.

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Sedgwick, P. "Stratified cluster sampling." BMJ 347, no. 22 3 (2013): f7016. http://dx.doi.org/10.1136/bmj.f7016.

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Saini, Monika, and Ashish Kumar. "Ratio estimators using stratified random sampling and stratified ranked set sampling." Life Cycle Reliability and Safety Engineering 8, no. 1 (2018): 85–89. http://dx.doi.org/10.1007/s41872-018-0046-8.

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Saunders, Ian W., and Geoffrey K. Robinson. "Restricted stratified random sampling." International Journal of Mineral Processing 25, no. 3-4 (1989): 159–66. http://dx.doi.org/10.1016/0301-7516(89)90015-x.

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THOMPSON, STEVEN K. "Stratified adaptive cluster sampling." Biometrika 78, no. 2 (1991): 389–97. http://dx.doi.org/10.1093/biomet/78.2.389.

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Stellingwerf, D. A., and S. Lwin. "Stratified sampling compared with two-phase stratified cluster sampling for timber volume estimation." Netherlands Journal of Agricultural Science 33, no. 2 (1985): 151–60. http://dx.doi.org/10.18174/njas.v33i2.16861.

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Two sampling methods were compared on orthophotos (scale 1:10 000) of a rectangular 12 855-ha area of intensively managed Norway spruce forest in Upper Austria. Trees other than spruce >40 yr old were ignored. 'Method 1' used stratified cluster sampling to determine the area proportion of spruce in the total area: 2 clusters of 5 circular 0.05-ha photo plots were randomly selected within each of 8 rectangular sub-blocks in each of 72 blocks into which the area was 'stratified' (systematically divided). Vol. was determined by 2-phase sampling: (i) 2 clusters were randomly selected in each bl
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Sisodia, B. V. S., Subedar Singh, and Sanjay K. Singh. "Calibration approach estimation of the mean in stratified sampling and stratified double sampling." Communications in Statistics - Theory and Methods 46, no. 10 (2016): 4932–42. http://dx.doi.org/10.1080/03610926.2015.1091083.

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Gui, Wenli, Liping Jing, Liu Yang, and Jian Yu. "Unsupervised Cross-Language Classification with Stratified Sampling-Based Cluster Ensemble." International Journal of Machine Learning and Computing 5, no. 3 (2015): 165–71. http://dx.doi.org/10.7763/ijmlc.2015.v5.502.

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Iliyasu, Rufai, and Ilker Etikan. "Comparison of quota sampling and stratified random sampling." Biometrics & Biostatistics International Journal 10, no. 1 (2021): 24–27. http://dx.doi.org/10.15406/bbij.2021.10.00326.

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The possibility that researchers should be able to obtain data from all cases is questionable. There is a need; therefore, this article provides a probability and non-probability sampling. In this paper we studied the differences and similarities of the two with approach that is more of fritter away time, cost sufficient with energy required throughout the sample observed. The pair shows the differences and similarities between them, different articles were reviewed to compare the two. Quota sampling and Stratified sampling are close to each other. Both require the division into groups of the
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Ryu, Jea-Bok, Jong-Min Kim, Tae-Young Heo, and Chun Gun Park. "On stratified randomized response sampling." Model Assisted Statistics and Applications 1, no. 1 (2005): 31–36. http://dx.doi.org/10.3233/mas-2006-1106.

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Dissertations / Theses on the topic "Stratified sampling"

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Platts, Alexander. "Functional quantization-based stratified sampling." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27105.

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Functional quantization-based stratified sampling is a method for variance reduction proposed by Corlay and Pagès (2015). This method requires the ability to both create functional quantizers and to sample Brownian paths from the strata defined by the quantizers. We show that product quantizers are a suitable approximation of an optimal quantizer for the formation of functional quantizers. The notion of functional stratification is then extended to options written on multiple stocks and American options priced using the Longstaff-Schwartz method. To illustrate the gains in performance we focus
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Zhong, C. X. Bob. "Empirical likelihood inference under stratified sampling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0032/NQ26890.pdf.

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Zhong, Bob Chongxin Carleton University Dissertation Mathematics and Statistics. "Empirical likelihood inference under stratified sampling." Ottawa, 1997.

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Ramalho, Esmeralda A. "Some sampling issues in econometrics." Thesis, University of Bristol, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248393.

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Liu, Jun Carleton University Dissertation Mathematics. "Inference from stratified samples: applications of Edgeworth Expansions." Ottawa, 1992.

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Vadrevu, Aditya M. "Random sampling estimates of fourier transforms antithetical stratified Monte Carlo /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p1450161.

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Thesis (M.S.)--University of California, San Diego, 2008.<br>Title from first page of PDF file (viewed Mar. 27, 2008). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 33-34).
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Sroka, Christopher J. "Extending Ranked Set Sampling to Survey Methodology." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1218543909.

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Gill, Abdul Aziz. "The use of stratified sampling to improve the performance of classification trees." Thesis, University of East Anglia, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.410087.

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In this thesis we study two primary areas for improvement in classification trees, namely accuracy and consistency of prediction. Classification trees are generally easier for humans to comprehend and have been used in a wide range of disciplines including medical sciences and statistics. This thesis reviews existing improvement techniques in detail and addresses those areas where the existing techniques show poor performance. Additionally, their strengths and weaknesses/ limitations in the light of statistical background have been investigated. Some important contributing factors towards impr
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Brown, Stephanie N. "A New Era of Educational Assessment: the Use of Stratified Random Sampling in High Stakes Testing." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407797/.

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Although sampling techniques have been used effectively in education research and practice it is not clear how stratified random sampling techniques apply to high-stakes testing in the current educational environment. The present study focused on representative sampling as a possible means for reducing the quantity of state-administered tests in Texas public education. The purpose of this study was two-fold: (1) to determine if stratified random sampling is a viable option for reducing the number of students participating in Texas state assessments, and (2) to determine which sampling rate pro
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Song, Chenxiao. "Monte Carlo Variance Reduction Methods with Applications in Structural Reliability Analysis." Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/29801.

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Monte Carlo variance reduction methods have attracted significant interest due to the continuous demand for reducing computational costs in various fields of application. This thesis is based on the content of a collection of six papers contributing to the theory and application of Monte Carlo methods and variance reduction techniques. For theoretical developments, we establish a novel framework of Monte Carlo integration over simplices, throughout from sampling to variance reduction. We also investigate the effect of batching for adaptive variance reduction, which aims at running the Monte Ca
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Books on the topic "Stratified sampling"

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Bedier, Mostafa Abdellatif. Post stratified estimation using a known auxiliary variable. Oregon State University, 1989.

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Campbell, P. Comparison of two methods commonly used at the experimental lakes area for collecting chemistry samples from vertically stratified lakes. Central and Arctic Region, Dept. of Fisheries and Oceans, 1993.

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Nielsen, G. A. Incorporating fixed and repeat sets in the stratified random survey for groundfish in the Southern Gulf of St. Lawrence. Dept. of Fisheries and Oceans, Science Branch, 1995.

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Scott, J. C. Computerized stratified random site-selection approaches for design of a ground-water-quality sampling network. Dept. of the Interior, U.S. Geological Survey, 1990.

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Jacobs, Steven E. Use of stratified random sampling to estimate the abundance of Oregon coastal coho salmon. Oregon Dept. of Fish and Wildlife, Fish Division, 1998.

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Robertson, E. O. Assessment of the value of stratified sampling for aerial surveys: A case study of bowhead whales in the Beaufort Sea. Central and Arctic Region, Dept. of Fisheries and Oceans, 1987.

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Zalinge, Nicholas van. Description of the shrimp fishery including a stratified sampling scheme for shrimp landings and effort at Karachi Fish Harbour: A report prepared for the Marine Fisheries Development, Karachi Project. Food and Agriculture Organization, 1987.

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Bakhshi, Ziaul Hassan. Stochastic Programming Approach in Stratified Sampling Problems: Stochastic Programming in sampling surveys. LAP LAMBERT Academic Publishing, 2015.

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Bedier, Mostafa Abdellatif. Post stratified estimation using a known auxiliary variable. 1989.

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Fisher, Scott W. A comparison of the basket method and stratified random sampling for contract change order negotiations. 1987.

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Book chapters on the topic "Stratified sampling"

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Lohr, Sharon L. "Stratified Sampling." In Sampling, 3rd ed. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429298899-3.

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Gooch, Jan W. "Stratified Sampling." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15393.

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Singh, Ravindra, and Naurang Singh Mangat. "Stratified Sampling." In Kluwer Texts in the Mathematical Sciences. Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-017-1404-4_5.

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Heppner, John B., David B. Richman, Steven E. Naranjo, et al. "Stratified Sampling." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_4423.

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Cohen, Michael P. "Stratified Sampling." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_574.

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Lu, Yan, and Sharon L. Lohr. "Stratified Sampling." In R Companion for Sampling. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003228196-3.

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Lu, Yan, and Sharon L. Lohr. "Stratified Sampling." In R Companion for Sampling. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003228196-3.

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Lohr, Sharon L. "Stratified Sampling." In SAS® Software Companion for Sampling. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003160366-3.

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Forsberg, Ole J. "Stratified Sampling." In Understanding Elections through Statistics, 2nd ed. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781032684550-4.

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Cohen, Michael P. "Stratified Sampling." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-69359-9_660.

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Conference papers on the topic "Stratified sampling"

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Kobayashi, Soya, Daisuke Fujita, Hironobu Shibutani, Shinsuke Gohara, and Syoji Kobashi. "ESWL Outcome Prediction with SMOTE and Stratified Sampling." In 2024 Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS). IEEE, 2024. https://doi.org/10.1109/scisisis61014.2024.10760074.

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Lyu, Chenyang, Wenxi Li, Tianbo Ji, et al. "Enhancing Video-Text Matching via Sparse Stratified Sampling." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10888493.

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Oladimeji, Olatunji Muhammad, Amos Adedayo Adewara, Femi Emmanuel Amoyedo, Ezekiel Olaoluwa Omole, Peter Onu, and Kehinde Peter Ajewole. "Improved Ratio Estimator under Stratified Simple Random Sampling Using Auxiliary Variable." In 2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG). IEEE, 2024. http://dx.doi.org/10.1109/seb4sdg60871.2024.10630033.

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Gowda, Vikas Thammanna, Mason Lee, and Vanessa Campagna. "Enhanced Stratified Sampling: A Method for Privacy Preserving Big Data Publishing." In 2024 IEEE International Conference on Future Machine Learning and Data Science (FMLDS). IEEE, 2024. https://doi.org/10.1109/fmlds63805.2024.00056.

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Chennareddy, Srihith, and Vamshi Krishna Appala. "Optimizing AI Model Training Costs with Stratified Sampling and Self-Adaptive Testing." In 2025 3rd International Conference on Advancement in Computation & Computer Technologies (InCACCT). IEEE, 2025. https://doi.org/10.1109/incacct65424.2025.11011465.

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Afolayan, Temitope, Amos Adedayo Adewara, Femi Emmanuel Amoyedo, Olaoluwa E. Omole, Peter Onu, and Kehinde Peter Ajewole. "An Enhanced Stratified Ratio and Product Estimators in Double Sampling Using Auxiliary Variable." In 2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG). IEEE, 2024. http://dx.doi.org/10.1109/seb4sdg60871.2024.10630417.

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Zhang, Yu-Ming, Jun-Wei Hsieh, Yu-Hsiu Chang, et al. "Set-Nas: Sample-Efficient Training For Neural Architecture Search With Strong Predictor And Stratified Sampling." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10647243.

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Cheung, Catherine, Alejandro Rubio, and Julio Valdés. "Data-Driven Classification of Ch-146 Manoeuvres Using Mems-Imu Sensor System." In Vertical Flight Society 73rd Annual Forum & Technology Display. The Vertical Flight Society, 2017. http://dx.doi.org/10.4050/f-0073-2017-12078.

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This paper describes the use of a low-cost standalone MEMS-IMU (micro-electromechanical system - inertial measurement unit) sensor system developed by the National Research Council Canada (NRC) for manoeuvre recognition in helicopters. The system records accelerations, angular rotation rates, magnetic flux, altitude, location and velocity through its IMU and GPS. The MEMS-IMU system was flown on the Bell 412 CH-146 Griffon helicopter in a series of scripted flights consisting of 60 manoeuvres and regimes from the helicopter's usage spectrum. A flight log recorded by passengers with detailed st
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Hatoum, Fahd T., Robert Tomek, Heather M. Whitney, and Maryellen L. Giger. "Importance of stratified sampling for use in the development of training and test sets: medical imaging AI applications." In Computer-Aided Diagnosis, edited by Susan M. Astley and Axel Wismüller. SPIE, 2025. https://doi.org/10.1117/12.3048942.

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Bennett, Paul N., and Vitor R. Carvalho. "Online stratified sampling." In the 19th ACM international conference. ACM Press, 2010. http://dx.doi.org/10.1145/1871437.1871677.

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Reports on the topic "Stratified sampling"

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Johnston, J. W., and L. J. Davis. Stratified random sampling plan for an irrigation customer telephone survey. Office of Scientific and Technical Information (OSTI), 1986. http://dx.doi.org/10.2172/5901206.

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Al Baghal, Tarek, and Alexandru Cernat. Introduction to Survey Sampling. Instats Inc., 2024. https://doi.org/10.61700/8snowjtedo8er1808.

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This two-day workshop provides an in-depth introduction to applied survey sampling, focusing on key techniques such as simple random sampling, stratified sampling, and cluster sampling. Participants will learn the theoretical foundations of sampling design, explore coverage and sampling errors, and understand the importance of appropriate sample frames in different contexts. By the end of the course, attendees will have a solid grasp of the nuances of population representation and frame selection, enhancing their ability to design credible and accurate surveys.
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Kott, Phillip S. The Degrees of Freedom of a Variance Estimator in a Probability Sample. RTI Press, 2020. http://dx.doi.org/10.3768/rtipress.2020.mr.0043.2008.

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Inferences from probability-sampling theory (more commonly called “design-based sampling theory”) often rely on the asymptotic normality of nearly unbiased estimators. When constructing a two-sided confidence interval for a mean, the ad hoc practice of determining the degrees of freedom of a probability-sampling variance estimator by subtracting the number of its variance strata from the number of variance primary sampling units (PSUs) can be justified by making usually untenable assumptions about the PSUs. We will investigate the effectiveness of this conventional and an alternative method fo
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Harter, Rachel M., Pinliang (Patrick) Chen, Joseph P. McMichael, Edgardo S. Cureg, Samson A. Adeshiyan, and Katherine B. Morton. Constructing Strata of Primary Sampling Units for the Residential Energy Consumption Survey. RTI Press, 2017. http://dx.doi.org/10.3768/rtipress.2017.op.0041.1705.

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The 2015 Residential Energy Consumption Survey design called for stratification of primary sampling units to improve estimation. Two methods of defining strata from multiple stratification variables were proposed, leading to this investigation. All stratification methods use stratification variables available for the entire frame. We reviewed textbook guidance on the general principles and desirable properties of stratification variables and the assumptions on which the two methods were based. Using principal components combined with cluster analysis on the stratification variables to define s
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ตั้งมณี, ชัชพงศ์, та อรุณี กำลัง. พฤติกรรมการเสพติดอินเตอร์เนตของนิสิตจุฬาลงกรณ์มหาวิทยาลัย : รายงานการวิจัย. จุฬาลงกรณ์มหาวิทยาลัย, 2002. https://doi.org/10.58837/chula.res.2002.23.

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การใช้อินเตอร์เนตส่งผลกระทบทั้งทางบวกและลบ ในขณะที่ผลกระทบทางบวก เช่น ค่าใช้จ่ายที่ลดลง การได้ข้อมูลที่เป็นปัจจุบันและทันต่อการตัดสินใจ หรือความถูกต้องรวดเร็วของการทำธุรกรรมออนไลน์ ได้เป็นที่รู้จักอย่างแพร่หลาย แต่ทว่าผลกระทบทางลบ เช่น การละเมิดสิทธิของข้อมูลส่วนบุคคล หรือการใช้อินเตอร์เนตจนถึงขั้นเสพติด ยังไม่เป็นที่รู้จักมากนัก โดยเฉพาะอย่างยิ่งผลกระทบทางลบในสภาพแวดล้อมของประเทศไทย งานวิจัยชิ้นนี้จึงมีวัตถุประสงค์หลักเพื่อ (1) รายงานภาวการณ์เสพติดอินเตอร์เนตของนิสิตจุฬาลงกรณ์มหาวิทยาลัยในระดับปริญญาตรีของหลักสูตรปกติ ทั้งในภาพรวมและแยกตามสาขาวิชาวิทยาศาสตร์ สังคมศาสตร์ และสาธารณสุขศาสตร์ และ
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van der Mensbrugghe, Dominique. The META 21 Integrated Assessment Model in GAMS and LHS Sampling. GTAP Working Paper, 2023. http://dx.doi.org/10.21642/gtap.wp95.

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The META 21 Integrated Assessment Model (Dietz et al., 2021) represents a fairly comprehensive climate change simulation model incorporating a number of features: (a) a recent simple climate model; (b) down-scaling of temperature change to the country level; (c) integration of a number of bio-physical tipping points linked to rising temperatures; and (d) economic damages linked to rising sea levels and temperature using recent country-level estimates from the literature. The original implementation of META 21 was in Excel and linked to the @Risk Excel add-in for performing Monte Carlo-type ana
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Idakwo, Gabriel, Sundar Thangapandian, Joseph Luttrell, Zhaoxian Zhou, Chaoyang Zhang, and Ping Gong. Deep learning-based structure-activity relationship modeling for multi-category toxicity classification : a case study of 10K Tox21 chemicals with high-throughput cell-based androgen receptor bioassay data. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41302.

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Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for in silico predictive toxicology than existing shallow learning algorithms. However, contradicting reports have been documented. To further explore the advantages of DL over shallow learning, we conducted this case study using two cell-based androgen receptor (AR) activity datasets with 10K chemicals generated from the Tox21 program. A nested double-loop cross-validation approach was adopted along with a stratified sampling strategy for partitioning chemicals of multiple AR
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Maloney, Megan, Sarah Becker, Andrew Griffin, Susan Lyon, and Kristofer Lasko. Automated built-up infrastructure land cover extraction using index ensembles with machine learning, automated training data, and red band texture layers. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49370.

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Automated built-up infrastructure classification is a global need for planning. However, individual indices have weaknesses, including spectral confusion with bare ground, and computational requirements for deep learning are intensive. We present a computationally lightweight method to classify built-up infrastructure. We use an ensemble of spectral indices and a novel red-band texture layer with global thresholds determined from 12 diverse sites (two seasonally varied images per site). Multiple spectral indexes were evaluated using Sentinel-2 imagery. Our texture metric uses the red band to s
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Shiihi, Solomon, U. G. Okafor, Zita Ekeocha, Stephen Robert Byrn, and Kari L. Clase. Improving the Outcome of GMP Inspections by Improving Proficiency of Inspectors through Consistent GMP Trainings. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317433.

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Approximately 90% of the pharmaceutical inspectors in a pharmacy practice regulatory agency in West Africa have not updated their training on Good Manufacturing Practice (GMP) inspection in at least eight years. However, in the last two years the inspectors relied on learning-on-the job skills. During this time, the agency introduced about 17% of its inspectors to hands-on GMP trainings. GMP is the part of quality assurance that ensures the production or manufacture of medicinal products is consistent in order to control the quality standards appropriate for their intended use as required by t
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Griffin, Andrew, Sean Griffin, Kristofer Lasko, et al. Evaluation of automated feature extraction algorithms using high-resolution satellite imagery across a rural-urban gradient in two unique cities in developing countries. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40182.

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Feature extraction algorithms are routinely leveraged to extract building footprints and road networks into vector format. When used in conjunction with high resolution remotely sensed imagery, machine learning enables the automation of such feature extraction workflows. However, many of the feature extraction algorithms currently available have not been thoroughly evaluated in a scientific manner within complex terrain such as the cities of developing countries. This report details the performance of three automated feature extraction (AFE) datasets: Ecopia, Tier 1, and Tier 2, at extracting
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